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IBM quantum computer
Cryptographically Relevant Quantum Computer Cryptography Cyber Security cybersecurity policies Enterprise security IBM quantum computer

Post-Quantum Cryptography Readiness Becomes a Strategic Cybersecurity Priority for Enterprises

 

Though practical quantum computers may still be years away, organizations are already preparing for the security risks they could create. Post-quantum cryptography has shifted from research into real-world planning as experts warn current encryption could eventually become vulnerable. Rather than waiting for that moment, many businesses are reviewing existing systems now. 

Early preparation is increasingly viewed as essential because delaying changes could make future transitions far more difficult. Fresh policies are adding urgency by setting clear expectations for organizations responsible for protecting critical infrastructure and sensitive data. Quantum readiness is no longer seen as only an IT issue but a business-wide priority involving leadership, governance, funding, and long-term planning. 

Instead of simply replacing outdated encryption, organizations are expected to build flexible strategies that can adapt to future cryptographic standards. A major concern is the “harvest now, decrypt later” threat. Attackers may steal encrypted information today and store it until quantum computers become powerful enough to decrypt it. 

Intellectual property, healthcare records, financial information, source code, and government communications with long-term value could all become exposed in the future, even if current encryption remains secure against today’s computers. The challenge is no longer just preparing for future technology but protecting data that must remain confidential for years. Organizations handling highly sensitive or regulated information may need to begin migration sooner because the consequences of delayed action could be far greater.  

Cybersecurity leaders recommend assigning clear ownership of post-quantum initiatives instead of leaving responsibility with individual application teams. Cross-functional groups involving security, IT, engineering, legal, compliance, procurement, and business leadership are better positioned to manage the transition since encryption supports nearly every part of modern digital operations. 

A critical first step is identifying where cryptography exists throughout the organization. Many companies lack a complete view of which systems rely on specific algorithms, certificates, keys, authentication methods, APIs, cloud environments, and third-party services. Without that visibility, assessing risks or deciding migration priorities becomes extremely difficult. Security experts also stress that this inventory should remain continuously updated rather than existing as a static spreadsheet. 

Ongoing visibility helps organizations identify systems requiring stronger protection, understand dependencies, provide accurate regulatory reporting, and give executives a realistic view of progress. Once cryptographic assets are fully mapped, organizations can prioritize migration based on business impact. Systems protecting customer information, healthcare data, financial services, critical infrastructure, digital identities, and software integrity generally require attention before less critical environments, allowing organizations to spread the transition over several years. 

Preparing for post-quantum security also requires dedicated investment. Funding must support discovery tools, testing environments, migration programs, automation, and governance. Organizations will also need specialists with expertise in cryptography, enterprise architecture, public key infrastructure, compliance, and cybersecurity to guide the transition effectively. Long-term success depends on achieving crypto-agility—the ability to update cryptographic algorithms without rebuilding entire systems. 

Rather than treating post-quantum cryptography as a one-time project, many organizations are designing adaptable security architectures capable of evolving alongside future standards. As artificial intelligence, autonomous technologies, and increasingly complex digital ecosystems continue to expand, flexible cryptographic infrastructure will become even more important.  

Although no one knows exactly when quantum computers capable of breaking today’s encryption will become reality, many cybersecurity experts believe organizations should begin preparing now. Companies that establish governance, maintain visibility into cryptographic assets, and gradually modernize their infrastructure will be better positioned to adapt as quantum computing—and the security landscape—continues to evolve.
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OpenAI Security
AI Security Model Cyber Defense AI Cyber Security Defensive AI Frontier AI Security GPT-5.5 Cyber GPT-5.6 OpenAI GPT-5.6 Sol OpenAI Security

GPT-5.6 Sol Debuts With Enhanced Cyber Protections, Limited to Trusted Partners


 

An open preview of OpenAI's next-generation GPT-5.6 model family has been introduced under tight control, marking an important milestone in the advancement of frontier artificial intelligence with an equal emphasis on cybersecurity and responsible deployment. The release is anchored by GPT-5.6 Sol, the company's most advanced and security-hardened model to date. 

It introduces a three-tier architecture comprising Sol, Terra, and Luna, each of which is specifically designed to meet distinct performance, cost, and deployment requirements in software engineering, scientific research, professional knowledge work, computer use, and cybersecurity. OpenAI has restricted access to its API and Codex platforms to a select group of trusted partners following a formal request from the Trump administration rather than releasing the technology to the general public immediately. 

As a result, a cautious strategy emphasizes rigorous security evaluation, controlled real-world testing, and resilience against misuse before the product is available in broad markets. 

GPT-5.6 Introduces a New AI Model Architecture

Moreover, OpenAI is transforming its product architecture, replacing sequential branding with permanent capability tiers in addition to its flagship launch. A long-term restructuring of OpenAI's model portfolio is also part of the GPT-5.6 release, replacing sequential branding with permanent capability tiers that differentiate performance, efficiency, and deployment. 

Sol is the flagship model for advanced reasoning and technical tasks within this framework, Terra delivers performance comparable to GPT-5.5 at approximately half the operational cost for enterprise-scale deployments, while Luna is designed to achieve low latency and low operating cost for high-volume inference applications. Instead of GPT-5.5, which emphasized reasoning and coding improvements, GPT-5.6 emphasizes defensive cybersecurity, controlled deployment, and capability-specific safeguards, reflecting the general trend toward the advancement of security-aware frontier AI. 

The company states that the phased deployment reflects ongoing engagement with federal authorities in an effort to align future frontier AI releases with the objectives outlined in the recent Executive Order governing the assessment of advanced artificial intelligence systems for national security purposes. 

Preparedness Framework Strengthens Cybersecurity Safeguards 

Security remains central to the GPT-5.6 rollout. In its Preparedness Framework, OpenAI has categorized Sol, Terra, and Luna as High Capability models for both cybersecurity, biology, and chemical domains. However, none of these models currently meet the threshold for AI self-improvement as a High Capability model. 

To reduce the increased dual-use risks associated with increasingly capable foundation models, the company has adopted capability-specific safeguards rather than a uniform protection layer in order to mitigate this risk. By combining policy-level restrictions with automated classifiers, cybersecurity- and biology-related prompts are continuously analyzed in real time through the security architecture. 

When potentially high-risk interactions are detected, response generation is temporarily halted until a secondary reasoning model reviews the conversational context to determine whether or not to allow or restrict responses. A risk assessment can also be conducted by OpenAI at an account level to help differentiate legitimate security research and vulnerability analysis from potentially malicious behavior. 

GPT-5.6 Sol Demonstrates Strong Defensive Security Performance

The OpenAI benchmark results demonstrate that GPT-5.6 Sol provides competitive performance in defensive cybersecurity tasks while operating with significantly higher computational efficiency as compared to GPT-5.6 Sol. Sol was able to achieve results comparable to those of leading frontier systems such as Mythos Preview when evaluated on ExploitBench with one-third more tokens required for output. 

In internal testing of large Chromium and Firefox codebases, the model demonstrated the capability of identifying software flaws, isolating vulnerabilities, and providing patching advice as well as basic exploitation primitives. In addition, OpenAI pointed out that the system did not independently develop complete multistage exploit chains, reinforcing its goal of supporting defensive security research rather than facilitating offensive cyber operations. 

Red-Teaming and Safety Testing Ahead of Deployment

The OpenAI preview version included more than 700,000 A100-equivalent GPU hours of automated red-teaming for further strengthening resilience against misuse. Rather than focusing solely on isolated prompt failures, the testing program targeted systemic weaknesses as well as universal jailbreak techniques capable of bypassing model safeguards across a variety of scenarios, thereby enhancing resilience against misuse. 

In the coming week, OpenAI plans to make the models available to a wider range of API and Codex partners. Additionally, OpenAI warns against making government-mediated pre-clearance a permanent requirement for frontier AI deployments. As a result of prolonged restrictions, advanced defensive capabilities may not be available as needed by the wider cybersecurity community to combat rapidly evolving threats if they are prolonged. 

Pricing, Capability Tiers and Enterprise Availability 

Additionally, OpenAI has revised its naming strategy with generation numbers identifying the model family, and Sol, Terra, and Luna remaining persistent capability layers. A tiered pricing structure based on token consumption has been established by the company, with GPT-5.6 Sol charging $5 for a million input tokens and $30 for a million output tokens, Terra charging $2.50 per input and $15 per output, and Luna charging $1 per input and $6 per output, in accordance with the performance profiles and deployment scenarios of each model. 

As part of OpenAI's ongoing commitment to the enterprise, GPT-5.6 Sol will be released on Cerebras in July, delivering inference speeds of up to 750 tokens per second for enterprises with high-throughput AI requirements. 

Government Oversight Shapes GPT-5.6 Rollout 

GPT-5.6's limited release has also been the focus of an ongoing debate concerning national security oversight of frontier AI systems as a result of the limited release. According to OpenAI, the decision was made to limit the initial release following the Trump administration's request for a staggered rollout as government agencies evaluated the impact of the model's advanced capabilities. 

Sam Altman, the Chief Executive Officer of OpenAI, has subsequently advised employees that access to the preview will be approved individually as part of the coordinated rollout process. The request was made in consultation with the Office of the National Cyber Director, the Office of Science and Technology Policy, and Howard Lutnick, Secretary of Commerce. 

It was openAI's belief that government-mediated access should continue to be an exceptional measure rather than a long-term deployment model, even as it cooperated with the temporary review process, arguing extended restrictions may deter developers, enterprises, and cybersecurity practitioners from implementing critical AI capabilities. 

New Reasoning Modes Expand Defensive AI Capabilities 

 Along with deployment and governance, OpenAI has also enhanced the defensive security capabilities of GPT-5.6. According to OpenAI, GPT-5.6 is designed to make prohibited offensive activities more difficult, uncertain, and detectable while preserving legitimate applications such as code review, vulnerability research, patch development, and defensive security testing. 

The Max Reasoning Effort mode introduced in GPT-5.6 supports this approach by allowing Sol to allocate considerable computational resources to complex problems before providing responses. With Ultra reasoning, the execution of long-term tasks which require sustained planning and multi-step analysis is enhanced beyond conventional single-agent execution by orchestrating multiple parallel subagents capable of collaborating collaboratively. 

Scientific Benchmarks and OpenAI's Cybersecurity Roadmap

GPT-5.6 is the latest model family from OpenAI that demonstrates the company's commitment to AI-based defensive cybersecurity. Additionally, the company recently introduced GPT-5.5-Cyber as part of its Daybreak initiative, a specialized model for automated vulnerability discovery, patch generation, and software remediation. 

The OpenAI model achieved state-of-the-art performance across CyberGym (85.6%), ExploitGym (39%), and SEC Bench Pro (69.8%), a significant improvement over GPT-5.5 baselines. Additionally, GPT-5.6 Sol has demonstrated improved performance on GeneBench v1 and improved reasoning efficiency, indicating that the latest releases are an integral part of a broader strategy: advancing frontier AI capabilities while also investing equally in tools and safeguards necessary for enhancing cyber defenses.
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Threat Intelligence
AI Threat Business Security Cyber Security Five Eyes Threat Intelligence

Five Eyes Warns New AI Models Pose Urgent Cyber Risk

 

The Five Eyes intelligence alliance has issued a stark warning that the latest generation of artificial intelligence could reshape the cyber threat landscape much faster than most organizations expect. In a joint advisory, intelligence and cybersecurity leaders from the United States, the United Kingdom, Canada, Australia and New Zealand said frontier AI models are advancing so quickly that long-standing assumptions about cyber risk may become outdated in only a matter of months. 

The message is clear: AI is no longer just a productivity tool or a research breakthrough. It is also a force multiplier for attackers who want to move faster, exploit weaknesses sooner and launch more sophisticated campaigns. According to the advisory, AI can lower the barriers for malicious actors by making phishing, malware development and vulnerability discovery easier and more efficient. 

That means attackers with limited technical skill may soon be able to carry out actions that once required experienced operators, while more advanced threat groups could automate parts of their workflow at greater scale. The intelligence chiefs said the risk is not theoretical, because the speed of AI development is already changing how quickly vulnerabilities can be found and weaponized. As a result, organizations that wait for mature standards may find themselves exposed before they realize the threat has changed. 

The alliance also emphasized that cyber risk should be treated as a business risk, not just an IT issue. Its guidance urges leaders to understand risk, strengthen foundational security controls and give cyber teams enough authority and resources to respond effectively. The warning stresses that breaches are inevitable, so preparedness matters as much as prevention. In practice, that means testing incident response plans, training staff and making sure the organization can contain and recover from an attack before it turns into a wider operational or financial crisis. 

Five practical steps were highlighted as urgent priorities: reduce unnecessary exposure, accelerate patching, address legacy systems, strengthen identity and access controls and prepare for incidents in advance. The advice is especially relevant because outdated systems and slow patch cycles remain common weaknesses across both public and private sectors. By limiting attack surfaces and tightening access, organizations can reduce the chances that AI-assisted attackers will find an easy opening. The core message is that resilience must be built before a crisis starts, not after. 

For businesses, the report is a reminder that AI’s cyber impact is arriving faster than policy and governance often do. The Five Eyes warning does not argue that AI should be avoided; instead, it says AI should be used deliberately to strengthen defense while leaders move faster on security basics. In other words, the organizations most likely to cope with AI-driven threats will be those that treat cybersecurity as continuous readiness, not a one-time compliance exercise.
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zhipu ai
AI Policy Artificial Intelligence China Cyber Security USA vulnerability zhipu ai

China's New AI Model Challenges U.S. Cybersecurity Leaders

 



China's latest open-weight artificial intelligence model is drawing attention within the cybersecurity community after independent evaluations indicated that it can rival some of the vulnerability detection capabilities of leading U.S. frontier AI systems. The findings are fueling renewed debate over whether restricting access to advanced American AI models is enough to slow the spread of powerful cyber capabilities.

Chinese AI company Zhipu AI, also known as Z.ai, released its GLM-5.2 model on June 13 under a permissive open-weight license. Unlike proprietary AI systems that are only accessible through controlled cloud services, open-weight models allow researchers and developers to download the model weights and run them on their own hardware. This approach enables offline deployment, customization through fine-tuning, and unrestricted experimentation without requiring ongoing approval from the model developer.

The release stands in contrast to Anthropic's Claude Mythos, one of several advanced AI systems whose availability has been limited under U.S. export controls because of concerns that highly capable models could be misused for offensive cyber operations. While GLM-5.2 still falls behind leading models from Anthropic and OpenAI across many general-purpose reasoning benchmarks, recent testing suggests it performs remarkably well in one highly specialized area: identifying software vulnerabilities.

Independent benchmarking conducted by Semgrep found that GLM-5.2 achieved an F1 score of 39% when detecting Insecure Direct Object Reference (IDOR) vulnerabilities. IDOR flaws arise when applications expose internal object identifiers without properly verifying whether a user is authorized to access the requested resource, making them a common source of unauthorized data access and privilege abuse. Under the same evaluation conditions, Claude Code recorded scores ranging from 32% to 37%, placing GLM-5.2 slightly ahead in this specific cybersecurity task.

The benchmark also underlined a notable economic advantage. Researchers estimated that GLM-5.2 identified vulnerabilities at an average cost of approximately $0.17 per finding, roughly one-sixth of the cost associated with comparable Claude-based workflows. Lower operating costs could make advanced AI-assisted vulnerability research accessible to a much broader range of organizations, independent researchers, and software security teams.

Additional benchmarking conducted by Graphistry reached similar conclusions, reinforcing the view that an openly downloadable Chinese model can compete with frontier U.S. AI systems in narrowly focused cybersecurity applications. The independent evaluations are particularly noteworthy because they relied on standardized testing methodologies designed to reduce benchmark contamination and minimize vendor-specific bias.

The findings arrive amid growing concern in Washington over the national security implications of frontier artificial intelligence. The Trump administration has increasingly treated advanced AI models such as Mythos and Fable as strategic technologies because of their ability to automate complex cybersecurity tasks, including discovering previously unknown software vulnerabilities that could potentially be weaponized in cyber operations.

Those concerns have shaped U.S. export control policies that restrict access to some advanced AI systems for foreign organizations, including researchers based in China. The underlying assumption behind these controls is that limiting access to the most capable American models would delay competing nations from acquiring comparable cyber capabilities. GLM-5.2's performance is prompting renewed questions about whether restricting model access alone can achieve that objective when capable alternatives are being developed elsewhere.

The discussion is further informed by Anthropic's Project Glasswing, which previously demonstrated the cybersecurity potential of frontier AI by identifying more than 10,000 critical software vulnerabilities during its initial research phase. The project illustrated how advanced language models can assist security researchers in reviewing large codebases, prioritizing weaknesses, and accelerating vulnerability discovery. If open-weight models begin approaching similar levels of performance, comparable capabilities may no longer remain exclusive to a small number of tightly controlled AI providers.

The latest development also comes shortly after OpenAI introduced GPT-5.6 with limited availability because of concerns surrounding misuse. Together, these decisions reflect a broader effort by U.S. AI developers to place increasingly capable models behind controlled access mechanisms while balancing innovation with national security considerations.

Cybersecurity researchers note that advances in open-weight models create opportunities as well as risks. Defensive teams could use these systems to automate code reviews, strengthen secure software development practices, and accelerate vulnerability remediation. At the same time, threat actors may attempt to exploit the same capabilities to identify weaknesses in software before organizations have an opportunity to patch them. Because GLM-5.2 can be downloaded and operated locally, these capabilities are available globally regardless of whether users have access to commercial U.S. AI services.

The emergence of GLM-5.2 does not necessarily indicate that Chinese AI has surpassed American frontier models across every benchmark. However, its strong performance in specialized cybersecurity evaluations suggests that the technological gap is narrowing in selected high-value domains. The development is likely to intensify debate over whether hardware restrictions and access controls alone are sufficient to preserve leadership in AI-driven cybersecurity, or whether future policy must place greater emphasis on strengthening defensive capabilities, accelerating software patching, and preparing for a world where advanced vulnerability discovery tools become increasingly accessible worldwide.

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Wireless Emergency Alerts
Cyber Security Emergency Alert System FCC cybersecurity Team Telecom undersea cable security Wireless Emergency Alerts

FCC Strengthens Cybersecurity Rules for Emergency Alert Systems and Undersea Cable Networks

 

The Federal Communications Commission (FCC) has approved a series of new regulations aimed at strengthening the cybersecurity of the United States' emergency communication systems while modernizing security requirements for the country's undersea cable infrastructure.

The newly adopted rules introduce stronger safeguards for the nation's two primary public warning platforms—the Emergency Alert System (EAS) and Wireless Emergency Alerts (WEA)—to reduce the risk of cyberattacks and unauthorized access.

The EAS is widely used by federal, state and local authorities to broadcast emergency information, including severe weather warnings, AMBER Alerts and other public safety notifications through television and radio networks. Meanwhile, the WEA delivers similar alerts directly to mobile devices through text messages.

According to the FCC, a successful cyberattack on either platform by a foreign government, cybercriminal organization or malicious actor could spread misinformation, create public confusion or disrupt emergency response efforts during critical situations.

Any vulnerability in systems like the Emergency Alert System “can have serious consequences,” said FCC Commissioner Olivia Trusty in a statement after the vote.

“That is why it has been appropriate for the Commission to conduct a comprehensive review of the EAS framework by focusing on the security of the system itself,” Trusty continued. “As cybersecurity threats continue to evolve, EAS participants must take appropriate steps to safeguard the infrastructure that supports the delivery of life-saving alerts.”

As part of the new cybersecurity framework, organizations responsible for operating EAS and WEA systems will be required to adopt stronger cyber hygiene measures. These include implementing robust passwords, promptly installing vendor-issued security updates and patches, and deploying firewalls to restrict unauthorized access to critical systems.

The FCC has also introduced a new authentication identification system that will verify emergency alerts before they are transmitted, helping prevent duplicate, fake or unauthorized alerts from being distributed.

In a separate decision, the Commission also approved its first major overhaul of submarine cable regulations in several decades. The updated framework seeks to enhance cybersecurity oversight for undersea cable infrastructure while simplifying licensing procedures for trusted operators.

Under the revised rules, certain undersea cable providers will no longer be required to undergo the extensive national security licensing review conducted by "Team Telecom" before operating cables connected to U.S. territory.

Team Telecom is an interagency group led by the Department of Justice's Foreign Investment Review Section, along with other federal agencies that evaluate the national security implications of telecommunications infrastructure.

The updated policy allows submarine cable applicants to qualify for an exemption if they can self-certify that they meet high security standards designed to improve certainty, streamline reviews and shorten licensing timelines.

“Currently, all submarine cable applications get referred to Team Telecom…the changes adopted would exempt applications from applicants that have operated cables without incident, can certify to the highest national security standards, and agree to ongoing oversight and monitoring,” the FCC said in a release.

The new regulations also expand the FCC's oversight of key operational components within submarine cable systems. Companies responsible for submarine line terminal equipment, which connects undersea cables to U.S.-based terrestrial facilities, will now be required to obtain licenses.

Additionally, the Commission has introduced updated security measures to address risks associated with essential equipment, third-party vendors and vulnerabilities across the broader submarine cable supply chain, further strengthening the resilience of critical communications infrastructure.

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Cyber Security
AI technology AI tools Anthropic Anthropic AI Anthropic Ban Claude Claude AI Cyber Security

Anthropic Restores Limited Access to Claude Mythos 5 AI Model After US Government Approval

 

Earlier limits on Anthropic’s top-tier AI tools have been eased by U.S. officials, reopening limited availability of the Claude Mythos 5 system to certain approved American institutions. Though only recently barred due to fears about potential misuse threatening national safety, the model is now accessible again under tight conditions. Government oversight in high-level AI deployment continues expanding, especially when such systems involve strong digital defense functions. 

While concerns remain, selective reinstatement suggests a shift toward managed access rather than blanket bans. Now cleared by U.S. authorities, Mythos 5 can be used again by groups managing essential infrastructure operations. Over a hundred entities - some among the largest corporations - are set to reconnect under new guidelines. Though access returns in phases, Anthropic emphasizes steady progress restoring function, even as talks continue with federal agencies on widening reach later. 

One goal remains: bringing back full public availability of the Fable 5 system after further review. One restriction began with an export directive dated June 12, forcing Anthropic to shut off entry points to Mythos 5 along with Fable 5. Not long after, OpenAI revealed a delay in launching GPT-5.6 widely - this pause came by direction from U.S. officials. Rather than open access freely, they handed early permissions only to select collaborators, names already passed to federal agencies.

Oversight like this signals a quiet but steady push from regulators to track how powerful artificial intelligence moves into real-world use. Officials worry powerful AI systems might fall into the hands of rival nations - like those in Beijing or Moscow - despite existing barriers. Because these tools can detect system flaws faster than humans, they may speed up digital attacks when protections fail. While designed for defense, their functions could shift toward offense once access is gained through weak points. 

Even infrastructure meant to resist intrusion becomes a target under such conditions. Surprisingly, Anthropic admitted that authorities questioned whether flaws in its security could allow bypassing controls meant to stop abuse of the Fable 5 system when spotting code weaknesses. Although officials noted improvements in handling those dangers, details about the specific defenses enabling partial revival of Mythos 5 remain undisclosed by public agencies. 

Though some defend the selection method, lawyers and tech executives have raised doubts. Questions emerge over who gets picked - free expression supporters point out unclear criteria behind group approvals. Without clear rules on checks, suspicion grows. Safety tests gain backing even as control worries surface; Sam Altman backs strong evaluations yet hesitates at state influence shaping access paths. Decisions made behind closed doors unsettle those watching closely. 

Now, trusted groups working with Mythros 5 won’t need export permits - this applies also to their staff outside the U.S. - as long as they’re named on the official roster. Still, firms left off the list must follow current licensing rules. A number of listed entities belong to Anthropic’s Project Glasswing, it is said, a collaboration hosting around one hundred tech outfits and study centers. 

Now comes news after Donald Trump issued an executive directive creating a non-mandatory process: creators of cutting-edge artificial intelligence may offer their systems to federal authorities for scrutiny during a thirty-day window prior to wider release. Some say this step offers temporary protection until more complete regulatory structures emerge through policy work. 

Yet concerns rise elsewhere - extended delays in launching powerful AI tools might hinder progress, weakening American firms just as international competitors push forward with their own intelligent technologies.
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signal
Backup CISA Cyber Security FBI Phishing signal

FBI Warns Russian-Linked Hackers Have Shifted Signal Phishing Campaign to Steal Backup Recovery Keys

 


The U.S. Federal Bureau of Investigation (FBI) and the Cybersecurity and Infrastructure Security Agency (CISA) have issued an updated public service announcement warning that Russian intelligence-linked threat actors have expanded an ongoing phishing campaign targeting Signal users. Rather than attempting to intercept authentication codes alone, the attackers are now seeking victims' Signal Backup Recovery Keys, enabling them to restore encrypted cloud backups and gain access to historical conversations.

The latest advisory builds on an alert released in March 2026, when the agencies disclosed that Russian-backed operators were targeting users of commercial messaging applications, particularly Signal, through carefully crafted phishing campaigns. Those earlier attacks focused on compromising accounts by deceiving users into handing over verification codes, account PINs, or linking unauthorized devices to their Signal accounts, instead of defeating the application's end-to-end encryption.

According to the FBI, the threat actors have refined their social engineering techniques by impersonating automated Signal support accounts and introducing a new objective: convincing users to disclose the recovery keys that protect their encrypted backups.

The agencies said the campaign continues to concentrate on individuals considered to be of intelligence value, including current and former U.S. government officials, government personnel from allied nations, military members, political figures, journalists, and officials located in Ukraine.

The activity has been attributed to Russian Intelligence Services (RIS), including officers associated with Russia's Federal Security Service (FSB) Border Guards and additional actors operating on behalf of the Russian military. Security researchers publicly track the activity under the designations UNC5792 and UNC4221.

Phishing campaign evolves beyond account hijacking

The updated advisory describes a notable change in the attackers' methods. Earlier phishing attempts largely sought one-time verification codes, Signal PINs, or persuaded victims to connect attacker-controlled devices to their accounts. The current campaign instead attempts to obtain the cryptographic recovery key used by Signal's Secure Backups feature.

To begin the attack, the operators pose as Signal's support team and distribute fraudulent messages claiming the messaging platform is introducing mandatory two-factor verification following an alleged increase in attacks carried out by hackers from Iran and post-Soviet countries. The messages falsely state that the security changes require users to configure Signal Backups in order to avoid losing conversations and media files.

Victims are instructed to navigate through the application's backup settings, enable Secure Backups, reveal the Backup Recovery Key, copy it to the clipboard, and complete what appears to be a legitimate setup process.

Signal's Secure Backups feature allows users to store encrypted copies of conversations on the company's cloud infrastructure. Those backups remain protected through end-to-end encryption, with the Backup Recovery Key serving as the only credential capable of decrypting and restoring the archived data. Because Signal does not retain this key, anyone who obtains it can restore the encrypted backup onto another device.

After victims complete the initial steps, the attackers send a second phishing message while continuing to impersonate Signal support. This follow-up communication claims the user's account is experiencing a synchronization problem and warns that stored messages and media could be permanently lost unless immediate action is taken.

The fraudulent notification instructs users to revisit the backup settings, copy the Backup Recovery Key once again, and paste it directly into the conversation under the pretense of preventing data loss.

If victims comply, the attackers obtain the recovery key and use it to restore the encrypted backup on devices under their control. This grants access to previously archived communications, including private conversations and group chats.

The FBI emphasized that these attacks do not compromise Signal's encryption itself. Instead, they rely entirely on social engineering techniques that manipulate users into voluntarily surrendering the credentials needed to decrypt their own backups.

Compromised recovery keys remain a risk even after creating a new account

The updated advisory also highlights a recovery scenario that affected users may easily overlook.

According to the FBI, creating a new Signal account with the same phone number does not invalidate a Backup Recovery Key that has already been stolen. If attackers previously acquired the key, they may still be able to access any encrypted backups downloaded before the compromise was discovered.

To prevent future backup restorations using a compromised credential, users should generate a new Backup Recovery Key through Signal's backup settings. Creating a replacement key invalidates the previous one for subsequent backup downloads. However, the agencies cautioned that this action cannot revoke access to backups that attackers have already restored using the stolen key.

Agencies urge users to remain cautious of unsolicited support messages

The FBI and CISA reminded users that legitimate messaging platform support teams communicate only through official company email channels. They do not request verification codes through the application itself, nor do they send unsolicited messages instructing users to verify accounts, restore backups, or disclose recovery credentials.

Anyone who believes they may have interacted with the phishing campaign is encouraged to report the incident to the FBI's Internet Crime Complaint Center (IC3), a local FBI field office, or CISA.

The advisory accentuates the fact that well-designed encryption remains effective only when the credentials protecting it remain under the user's control. Rather than attempting to break modern cryptography, state-sponsored threat actors are increasingly directing their efforts toward manipulating trusted users into revealing the keys that unlock their own protected data.

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Infrastructure Security
AI Infrastructure Security AI Security Credential Cyber Security Enterprise AI Security Enterprise security Infrastructure Security

AI Credential Security Emerges as Critical Risk in Modern Enterprise Infrastructure

 

Surprisingly, artificial intelligence alters how companies build their internal systems. Yet warnings emerge - not about flawed code, but about access methods growing more dangerous by the day. Credentials like API keys, login tokens, or automated service IDs now attract attackers as firms adopt more AI tools. 

A new report highlights an odd trend: defenses focus on outer boundaries, though weak identity controls often cause breaches inside AI environments. Investment flows into firewalls, even when real threats hide within permission structures Security breaches lately show a shift: criminals now aim more at login details instead of bugs within AI tools. A known example occurred when hackers gained access to publishing rights for a software library, slipping in harmful updates that collected AI account passwords, cloud keys, and system tokens across infected setups. 

Elsewhere, hidden project files left public helped adversaries grab artificial intelligence API secrets - before any code ran. Attackers succeeded here by abusing leaked authentication data, not defects in the underlying AI frameworks One reason experts point to is deeper issues baked into how AI systems are built. Instead of isolated logins for narrow tools, today’s setups often let one key open doors across many models and platforms. Because of this shift, losing control of login details means much wider exposure. Stolen tokens now offer criminals far greater leverage than before Among recent findings, signs point to an expanding problem with stolen login details.

A study across sectors showed over 1.27 million credentials tied to artificial intelligence services spilled online in 2025 alone - an uptick compared to prior periods. Old access tokens, though outdated, often stayed valid well beyond issue dates; when such keys fell into the wrong hands earlier, risk lingered far longer than expected Still, old-style safeguards like changing passwords, locking secrets away, or running automatic checks hold value - even if they fall short in AI-driven settings. 

Credentials tied to artificial intelligence tend to appear inside container files, system blueprints, build processes, recorded outputs, along with various hosted platforms. Once leaked access keys get found or reset, harm might already be done - copies hidden elsewhere, misuse underway. What worked before now lags behind how fast these systems share and replicate trust tokens Most security experts suggest companies start viewing AI identifiers much like those assigned to people or devices - restricting access based on necessity. 

Instead of using one wide-reaching API key, authorization should match only the needed tools, functions, or tasks. Each environment - whether used for live operations, trials, data review, or public interaction - ought to have distinct login details. This separation helps contain damage if one set gets exposed Security grows sharper when teams watch systems without pause. 

Ownership of access keys must be obvious, someone always accountable. Seeing what runs at any moment helps spot odd behavior early. Frequent checks on user actions reveal risks before they spread. A login seen outside usual patterns? Treat it as breached, just in case. With AI spreading through daily workflows, tracking who can do what matters more each month. Identity rules once tucked behind firewalls now step forward. They anchor defenses instead of trailing behind. Trust shifts only when proof holds firm.
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