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Showing posts with label Cyber Security. Show all posts

Citizens Bank, Stanford Warn Against Sharing Financial Data With AI

 

Artificial intelligence is quickly becoming part of everyday financial decision-making, but experts are warning Americans to be careful about what they share with it. Citizens Bank has stressed that AI can be helpful, yet it also brings serious privacy and fraud risks when people enter personal financial information into chatbots and similar tools. 

The biggest concern is oversharing. Many users ask AI for budgeting help, debt advice, or retirement guidance and then unknowingly provide account numbers, balances, income figures, tax details, or other sensitive data. According to reporting on Stanford-related research, sensitive information shared with AI systems may be stored, collected, or exposed through vulnerabilities, creating opportunities for identity theft or financial fraud. 

Citizens Bank says AI should not be treated like a secure financial adviser. Its online safety guidance warns that AI can be used by cybercriminals to steal money or identities, especially when users reveal critical information. The bank advises people to avoid sharing key financial details, use caution with suspicious messages, and verify anything that seems unusual through trusted sources rather than replying directly. 

Experts say there are safer ways to use AI for money questions. Instead of typing exact figures, users can describe their situation in broad terms or use ranges, such as “low savings” or “moderate debt,” to get useful guidance without exposing private data. This approach allows AI to give practical responses while reducing the chance that confidential information will be stored, reused, or leaked later.

According to security experts, AI can be a useful assistant, but it should never become a place to dump your personal finances. Americans who want to protect themselves should avoid entering banking credentials, account balances, Social Security numbers, or tax documents into any AI tool. In an era of growing AI-driven scams, caution is no longer optional — it is part of basic financial security.

Ad Tracking Puts US Troops at Risk on the Battlefield

 

The ad-tracking industry is facing fresh scrutiny after reports said commercial location data has been used to expose US soldiers in active war zones. US Central Command reportedly confirmed that it has received multiple threat reports about adversaries exploiting this data to target or surveil American personnel in theater. What began as a routine part of online advertising has now become a battlefield concern, showing how everyday mobile tracking can turn into a national security risk. 

At the center of the problem is a vast ecosystem of apps, brokers, and intermediaries that collect location signals from smartphones and other devices. This data is often sold through complex ad-tech pipelines, where device IDs, GPS points, and behavioral signals can be packaged and resold many times over. Even when users disable location settings, officials warn that geolocation may not be fully switched off on some commercial products, leaving sensitive traces behind. For military personnel, those traces can reveal patterns of life that make them easier to watch, map, or attack. 

The warning is especially serious because location data can help adversaries identify where troops congregate and infer operational routines. According to the reporting, such information could be used to support missile, drone, roadside bomb, or counterintelligence operations. That makes an ordinary privacy issue suddenly a security issue, since the same tracking systems used to deliver personalized ads can also expose people in conflict zones. 

Lawmakers have responded by pressing the Pentagon to strengthen protections on military devices and reduce exposure to tracking systems. Privacy advocates have long argued that the ad-tech sector creates a massive reserve of sensitive data that can be abused by both criminals and governments. Earlier incidents, including public mapping of military activity through fitness trackers, showed that location leaks are not theoretical. The new concern is that the same weaknesses may now be affecting troops in active combat areas at scale.

The broader lesson is simple: data collected for convenience can become dangerous when it falls into the wrong hands. For civilians, that means rethinking app permissions and privacy settings; for militaries, it means treating commercial tracking data as an operational threat. As the line between advertising technology and intelligence gathering keeps blurring, the ad industry may need far stricter rules on what it collects, sells, and shares.

Deno Releases Open-Source Firewall to Limit AI Agent Access to Sensitive Data

Deno has introduced an open-source security framework called Claw Patrol, a tool designed to help organizations control how AI agents interact with databases, business applications, cloud services, and other external systems.

The release comes as companies increasingly deploy AI agents to perform tasks that involve accessing internal resources, executing commands, and communicating with third-party services. While these capabilities can automate routine work, they also create security concerns if an AI system is manipulated, makes an incorrect decision, or gains access to information it should not handle.

According to Deno, Claw Patrol operates as an intermediary between an AI agent and the systems it needs to access. Instead of providing the agent with direct access to credentials such as API keys, authentication tokens, or database passwords, those secrets remain stored on a dedicated gateway server. When an authenticated request is required, the gateway supplies the credentials automatically, preventing the AI agent from viewing or storing them.

This approach is intended to reduce the risk of credential theft and prompt injection attacks, a technique where attackers attempt to manipulate AI models into revealing sensitive information or performing unauthorized actions. Even if an agent is tricked into executing a malicious instruction, the underlying credentials remain isolated from the model itself.

Beyond protecting credentials, Claw Patrol gives administrators the ability to define rules that determine exactly what actions an AI agent is allowed to perform. Organizations can block potentially dangerous database commands, restrict connections to unauthorized external services, or require additional approval before sensitive operations are executed.

For tasks that carry greater risk, the platform supports human review workflows. This allows certain requests to be paused until they are approved by an administrator, adding an additional layer of oversight before changes are made to critical systems.

Deno also states that the firewall can use large language model-based evaluation to assist with policy enforcement in situations where static rules may not be sufficient. This enables security controls to assess requests dynamically while still operating within predefined boundaries established by administrators.

To help organizations monitor AI activity, Claw Patrol includes tools that provide visibility into agent behavior. Administrators can review active sessions, inspect actions performed by agents, monitor resource consumption, and investigate unusual activity through a centralized monitoring interface. These capabilities are designed to support auditing and incident response efforts.

The platform is configured using HashiCorp Configuration Language (HCL), which allows administrators to define security policies, credentials, access permissions, and system endpoints. Deno says the framework supports multiple credential types and can be extended through custom plugins to meet specialized requirements.

Claw Patrol also incorporates role-based access controls, enabling organizations to assign permissions according to job responsibilities. This helps limit access to sensitive resources and reduces the likelihood of unauthorized activity within AI-powered workflows.

For secure communications, the platform can integrate with technologies such as WireGuard and Tailscale, allowing AI agents to connect to protected environments without exposing internal infrastructure directly to public networks. Deno has also included testing capabilities that allow administrators to evaluate policy changes against real-world actions before deploying them into production systems.

While the project introduces several security-focused capabilities, some challenges remain. Organizations unfamiliar with firewall administration or HCL-based configuration may face a learning curve during deployment. The current version also relies heavily on configuration files, and some users may prefer a graphical interface for managing rules and credentials. Additionally, certain networking features may require further refinement as the project matures.

Despite these limitations, the release reflects a growing focus on AI security as autonomous systems gain broader access to enterprise environments. By separating credentials from AI agents, restricting actions through policy controls, and providing continuous monitoring, Claw Patrol aims to give organizations greater control over how AI systems interact with critical business resources.

The project has been released as open-source software, allowing developers and security teams to inspect its code, modify its capabilities, and adapt it to their own operational requirements.

Americans Back Surveillance Pricing Ban Amid Growing Privacy and Consumer Cost Concerns

 

Ahead of schedule, more people in the U.S. resist price tracking based on private information - details like where they shop, what they buy, or how often they spend. Because companies gather these patterns, each customer might face different costs for the same item. Although firms have used such methods before, fresh survey results show resistance gaining strength now. Despite quiet implementation earlier, citizens appear less willing lately to accept unseen adjustments shaped by their own data. 

A recent poll from GBAO Strategies shows public worry over how monitoring-based pricing might affect household expenses, especially food bills. While examining attitudes, it emerged that two-thirds think data-driven pricing models may push grocery costs higher. In contrast, nearly as many see risks in electronic shelf labels that let stores adjust prices instantly. Rather than accept these systems, most people lean toward intervention - about 67 percent back a full prohibition. Such views highlight unease with automated pricing methods shaped by customer tracking. 

Across party affiliations, resistance to tracking-based price adjustments emerged clearly. Most Democrats, those unaffiliated with either major party, and Republicans backed legal restrictions, showing suspicion of algorithmic cost calculations cuts through ideological boundaries. Uneasiness around how stores gather personal details to shape what people pay appears widespread. What worries privacy supporters isn’t just what things cost. The Electronic Frontier Foundation points out how much private detail is needed for tracking-based price models. Systems tap into details like age, where someone lives, their online activity, past buys - sometimes even race or gender. 

Using such data to set prices, some say, puts personal secrecy at risk. Questions also emerge around whether the process plays fair - and if anyone can truly see how it works. Some shoppers might already be experiencing such tactics, according to available data. Back in 2025, a probe by Consumer Reports uncovered disparities in item costs during an Instacart trial using artificial intelligence for pricing. Identical products carried distinct price tags depending on the user viewing them. 

At times, differences climbed up to one-quarter more than others paid. Although mentioned in internal presentations meant for business stakeholders, most buyers did not know adjustments were happening behind the scenes. Most times, people talk about surveillance pricing together with dynamic pricing - both shaped by algorithms in retail settings. Shaped by demand shifts, stock availability, or broader economic climates, prices shift under this model. 

Firms like Amazon and Walmart already apply forms of this method. Even though personal information plays a smaller role here, actions taken by shoppers - their habits, past buys - still guide how prices are set. Though talk grows louder, officials now question if tighter rules must follow. 

Because worries stretch across spending habits alongside personal data risks, how stores track buyers shapes wider talks on fairness and control. While some argue restraint matters more, others see unchecked patterns where price shifts tie too closely to who is watching.

Android Spyware ‘Asin’ Uses Fake News and Utility Apps to Target Arabic-Speaking Users




Researchers at ESET have identified a previously undocumented Android spyware strain called Asin that is being distributed through fraudulent websites aimed at Arabic-speaking users.

According to the security company, the activity was first observed in early 2025 and involved several separate campaigns. The operators used different websites during each phase of the operation, presenting them as legitimate services to encourage users to download malicious Android applications.

Among the websites identified by researchers was govlens[.]net, which was registered in May 2025 and presented itself as a government-related news platform. Another site, pdf-reader[.]help, registered two days later, claimed to provide secure PDF viewing and editing capabilities. A third domain, live-war-map[.]com, registered in January 2025, advertised itself as a source of information about military incidents and conflict activity.

ESET found that some of these websites were promoted through social media accounts on Facebook and Telegram. The campaign's Telegram presence appeared to draw inspiration from Live Universal Awareness Map (Liveuamap), a legitimate service widely used to monitor armed conflicts, humanitarian crises, natural disasters, human rights developments, and geopolitical events around the world.

While the websites offered services that appeared useful or relevant to their intended audience, the downloaded applications contained hidden spyware components. Researchers said the malicious apps combined advertised functionality with surveillance capabilities operating in the background.

Additional evidence suggests the campaign remained active beyond its initial discovery. ESET identified several artifacts linked to Asin, including a sample uploaded to VirusTotal from Türkiye in October 2025. Another malicious Android package was downloaded from the domain c-pdf[.]net in December 2025 by a user operating a Xiaomi Redmi Note 13 Pro running Android 15.

Researchers also revealed a separate application disguised as Syria Defense Map. That sample was detected on a Xiaomi Redmi Note 13 Pro+ 5G device using Android 15 around mid-January 2026. In that case, the application was reportedly obtained through the website syriadefensemap[.]com.

As with many Android threats distributed outside official app marketplaces, users must manually install the software before it can operate. The spyware also relies on victims granting requested permissions, which can provide access to sensitive information stored on the device.

ESET has not attributed the activity to any known threat group, and the purpose behind the operation remains uncertain. However, the themes used throughout the campaign provide some indication of who may have been in the attackers' sights.

The company noted that three of the fraudulent applications, GovLens, WarMap, and Syria Defense Map, appear particularly relevant to individuals involved in open-source intelligence (OSINT) research. Because the applications focused on news gathering, conflict tracking, and investigative information, researchers believe Arabic-speaking journalists and OSINT practitioners may have been among the intended targets.

The findings illustrate how threat actors continue to package malicious code within applications that appear credible and useful. By exploiting interest in current events, government information, and conflict monitoring, attackers increase the likelihood that users will install software capable of collecting data from their devices without raising immediate suspicion. 

Google Employee Charged After Allegedly Using Confidential Search Data to Win $1.2 Million on Polymarket

 

A person working at Google stands charged with misusing private internal data to make winning predictions online - profits reportedly surpassing $1.2 million. In Manhattan, federal authorities say access to unreleased insights about what people search was leveraged improperly; outcomes linked directly to Google's own ranking movements. While performing regular job duties, the individual allegedly monitored patterns not meant for public view, then applied that knowledge elsewhere. Bets placed on future trends were informed by information obtained through employment. 

The case centers on whether insider awareness crossed into illegal territory when used outside corporate boundaries. Though common tools were involved, their application in forecasting events raised legal concerns. What began as routine work activity appears to have branched into personal financial gain. Investigators emphasize timing and access as critical elements under review. Working at Google as an information security engineer, Michele Spagnuolo reportedly gained access to user interaction logs tied to search activity. With such access came the ability - allegedly - to observe patterns others could not. 

From there, it is claimed he placed multiple wagers on Polymarket, where event-based predictions are monetized. The charges stem from a federal filing stating those trades relied on nonpublic insights. Though meant to remain confidential, the data supposedly guided his entries on the betting site. Each transaction appears linked to specific shifts in public interest tracked internally at Google. What followed was scrutiny when usage anomalies matched his market moves. It is claimed by investigators that Spagnuolo leveraged private data on Google searches to forecast movements tied to the company's yearly ranking releases. 

Because he had clearance to sensitive corporate details, prosecutors argue, he was aware of outcomes ahead of official announcements. With such insight came an edge - bets were made under conditions most market participants could not replicate. His position reportedly created opportunities far beyond what typical traders experience. Later came confirmation - Google's 2025 search data showed D4vd ranked highest by public interest. That result lined up exactly with a gamble made earlier under the alias "AlphaRaccoon." The bet had favored musician D4vd despite slim odds offered on prediction platforms. Authorities now connect Spagnuolo to that username. Before the list dropped, few expected such an outcome. Profits surged after the official release. 

Unlikely forecasts sometimes pay off, especially when timing aligns. Funds from successful trades reportedly added up to about $1..2 million, according to federal authorities. Following the influx of money, Spagnuolo began altering records - shifting details around - to mask who really controlled the accounts. Behind these actions lay an attempt, officials claim, to cover up improper use of confidential data. Prosecutors filed charges over commodities fraud, followed by wire fraud, along with money laundering accusations. 

Held in New York, Spagnuolo - an Italian national - gained release after posting a $2.25 million bond backed not only by cash but also by additional financial assurances as legal proceedings continue. When questioned about the claims, Google mentioned working alongside law enforcement. While workers may access certain internal systems normally, turning private data into gambling material crosses clear policy lines, according to the firm. 

Following review procedures, the individual involved was temporarily removed from duties until outcomes are determined. Two big court cases this year in New York target Polymarket, showing growing scrutiny. Behind the scenes, officials are digging into ways secret data might sway betting odds on forecasts. Questions grow about whether stronger rules should block insiders from exploiting these platforms. What happens next could reshape how such markets operate under watch.

Microsoft Adds Automated Endpoint Isolation to Strengthen Cyber Defense


Microsoft is advancing its automated cyber defence strategy with the release of Microsoft Defender for Endpoints, which is capable of isolating compromised devices as soon as malicious activity is detected. 


The feature was introduced as a preview and has been designed to curb the most damaging stage of an intrusion by preventing endpoints from connecting to the broader corporate network while maintaining a secure connection to Microsoft's Defender service. By integrating this capability into the automatic attack disruption framework, the company hopes to accelerate containment, reduce the attacker's operating window, and provide security teams with valuable time for investigation and remediation during the critical early moments of a breach without relying solely on manual interventions. 

In spite of Microsoft's assertion that automated response systems can be deployed quickly in the event of active intrusions, security researchers caution that they must be implemented with carefully defined safeguards. Microsoft introduced the feature earlier this month as part of ongoing enhancements to Microsoft Defender, though a timeline for general availability has not yet been provided. 

In addition, a recent SANS Institute report outlined a potential risk scenario in which threat actors could manipulate automated disruption workflows to interfere with administrator accounts, potentially resulting in difficulties during incident response. According to Johannes Ullrich, Dean of Research at SANS Institute, automated isolation and attack disruption technologies have existed in both commercial and open-source security platforms for years, yet their effectiveness relies heavily on how they are configured and tuned. 

As Ullrich points out, organizations with limited security resources will significantly benefit from automated containment, however poorly configured policies may allow attackers to delay remediation by targeting privileged accounts, leading to delayed remediation. Nonetheless, industry experts agree that automation has become increasingly important as ransomware and malware operations continue to execute at machine speed. 

According to Robert Enderle, when a human analyst detects malicious activity, adversaries might have already established persistence, expanded their foothold, or begun encryption of data by the time he identifies it. Through the introduction of the new capability, Microsoft Defender XDR addresses this gap by automatically isolating workstations that are subject to ransomware or advanced intrusion activity upon detection of high-confidence indicators. 

While the network access is severed to prevent command-and-control communications, lateral movement, and data exfiltration, the endpoint is still connected to Microsoft Defender services, which enables continuous telemetry collection, remote investigation, and forensic analysis. The functionality is currently restricted to managed devices enrolled in Microsoft Defender for Endpoint and does not yet extend to servers or unmanaged assets. 

In addition to integrating signals from endpoints, identities, email environments, and SaaS applications, Defender XDR creates a comprehensive incident view by correlating signals across these technologies to trigger containment actions when malicious activity reaches a certain level of confidence. 

With a focus on isolated devices rather than wider network segments, the platform aims to contain threats with minimal operational impact, while reducing the potential for ransomware to spread throughout an organisation. In addition to operational safeguards built into the feature, Microsoft has also implemented measures to ensure that aggressive containment measures do not disrupt business operations in an unnecessary manner.

At present, only end-user workstations that have been onboarded through Microsoft Defender for Endpoint are capable of automatic isolation, with security teams remaining in control of remediation decisions once investigations are completed and threats have been mitigated.

Defender portal administrators have immediate control over recovery actions, as they can release devices directly from the Device Inventory or through the individual device management page. This latest development is a continuation of Microsoft's ongoing commitment to endpoint containment, a strategy that has steadily grown over the past several years. 

By June 2022, Defender introduced manual containment capabilities for unmanaged Windows devices, enabling administrators to prevent inbound and outbound communication from Defender-protected endpoints that are compromised. In early 2023, support for isolating onboarded Linux devices began testing, and general availability was expected later that year. 

The Microsoft Corporation has subsequently extended its automatic attack disruption framework to include user account isolation, a measure aimed at preventing lateral movement during the exploitation of hands-on-keyboard ransomware attacks. As part of an ongoing evaluation of Defender for Endpoint enhancements, the company is currently testing automatic traffic blocking for previously undiscovered Windows devices, thereby reducing the possibility of attackers pivoting to unprotected devices within a network. 

The Microsoft company has also provided an overview of scheduled antivirus scanning for Linux-onboarded systems, in addition to these containment-focused developments. Administrators can schedule quick or full scans recurring through the Defender portal, managed JSON configurations, or command-line controls, with options for low-priority execution, idle-time scheduling, and randomised scans. 

Providing flexibility through automated recovery, administrator-driven release controls, exclusion policies for business-critical assets, and targeted containment logic that isolates only systems that are directly associated with malicious activity is a major component of the new automated isolation framework. 

Throughout the Microsoft Defender portal, all isolations, restorations, and response actions are recorded, and security teams can review detailed event timelines, trigger detections, and automated remediation activities through centralised investigation and action management interfaces. 

In a world where speed of detection is no longer sufficient without equally rapid containment, Microsoft's latest move highlights a broader shift in enterprise security. With threat actors increasingly automating intrusion, ransomware deployment, and lateral movement, organisations are increasingly relying on security platforms capable of determining the appropriate response in real time based on their high level of confidence.

However, the effectiveness of such automation ultimately relies upon its careful implementation, ongoing validation, and clearly defined operational safeguards. The challenge for defenders is not simply adopting autonomous security capabilities, but also ensuring they remain accurate, transparent, and aligned with corporate objectives. Success in cyber resilience is determined by finding the right balance between speed and control.

AI Cybersecurity Tools Raise Questions About the Future of Ethical Hacking Competitions

 

Surprisingly, artificial intelligence is changing cybersecurity faster than expected. Some elite ethical hackers now wonder whether human-driven hacking contests will stay relevant much longer. Momentum built around this idea when someone prominent at Pwn2Own this year pointed to advanced AI systems possibly surpassing numerous expert analysts. Performance gaps might widen as these tools grow stronger. 

Among those who took part in Berlin’s yearly Pwn2own contest, Valentina Palmiotti stood out - not just by name but by result. Though many go by handles online, she competes under the tag “Chompie,” a nickname familiar across security circles. Success came her way more than others’, marking her top among solo entrants. Instead of waiting for flaws to be misused, the event encourages finding hidden bugs first. Rewards follow when researchers expose weaknesses in digital tools that were not yet public knowledge. 

This year’s competition handed out close to $1..3 million for spotting 47 previously unknown weaknesses in various software and systems. Because researchers shared the details with makers first, fixes arrived ahead of potential exploitation. Midway through the event, Chompie exposed weaknesses across several platforms - some tied to Nvidia - securing significant rewards. Her method? Endless stretches of probing flaws, something she laughed about calling "zombie hacker mode," where nights blurred into days thanks to sheer persistence and concentration. 

Though today's AI tools speed up code analysis and threat detection, Chompie sees a shift on the horizon. Her view: present systems boost efficiency, yet future versions may make several classic roles obsolete. What now requires teams might soon run on smarter algorithms alone. Nowhere has scrutiny been more intense than around Claude Mythos, a powerful AI said to detect vast quantities of software weaknesses. The creators state it has uncovered countless security issues spanning many applications. Because of risks tied to abuse, only certain government bodies and cyber defense groups are allowed to use it. Access remains tightly controlled amid ongoing debate. Some scientists see things differently. 

A top Pwn2-Owned champion, Orange Tsai of Taiwan, treats artificial intelligence as a helpful tool instead of a substitute for people's knowledge. Because it speeds up testing, new approaches get checked faster - this means more attacks can be studied quickly. Still, originality, gut instinct, and sideways leaps in logic stay within human reach only; these traits often spot flaws machines miss. Though tech advances, certain mental moves resist automation. 

Though artificial intelligence is advancing, hackers now employ automation more often to speed up tasks like scanning networks, crafting phishing messages, or building malicious software. Yet a large number of breaches continue depending on older methods - manipulating people or stealing login details - instead of exploiting cutting-edge flaws. 

Even with worries over automation, some specialists think artificial intelligence might boost digital defense by spotting flaws more quickly than hackers can act. Because systems evolve fast, teams protecting networks may rely on smart tools to stay ahead - provided those resources are used carefully and shared wisely.