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Google Gemini Android Hijacked by Indirect Prompt Injection

Google Gemini Android Hijacked by Indirect Prompt Injection

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 9.1 The Hacker News

SafeBreach researcher Or Yair demonstrated that malicious text embedded in WhatsApp, Slack, SMS, or Signal notifications could trigger indirect prompt injection against Google Gemini's Android Utilities feature, causing the assistant to execute real device actions without user awareness. A novel bypass technique called 'Fake Context Alignment' defeated Google's post-patch authorization checks by exploiting multilingual obfuscation and muted hyperlinks to trick victims into authorising sensitive actions. Google has patched the issue, but the research exposes a fundamentally large attack surface where any app capable of pushing a notification becomes a potential injection vector.

Adversa AI: 89% of AI Agents Fail Security Tests

Adversa AI: 89% of AI Agents Fail Security Tests

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.2 SecurityWeek

Adversa AI's AI Risk Quadrant report evaluated 100 AI agents across ten categories, finding that only 11 qualify as both capable and well-defended. The research identifies a structural 'power-protection inversion' where the most capable agents also present the widest attack surface, driven by a 'lethal trifecta' of private data access, exposure to untrusted content, and outbound action capability. Computer and coding agents showed the most severe exposure, raising urgent concerns about autonomous agent deployment in enterprise environments.

Claude Sandbox Escape Enables Credential Exfiltration

Claude Sandbox Escape Enables Credential Exfiltration

ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 7.2 Simon Willison

Anthropic has published detailed documentation of its sandboxing architecture across Claude.ai, Claude Code, and Claude Cowork, including disclosure of a previously identified credential exfiltration vector via the api.anthropic.com/v1/files endpoint. The writeup covers process-level isolation technologies including gVisor, Seatbelt, Bubblewrap, and full VM approaches, and candidly acknowledges security gaps that were missed. This transparency is notable for the agentic AI space, where sandbox documentation is typically sparse and trust is difficult to calibrate.

CogCAPTCHA30 Fingerprints AI Agents via Behavioral Analysis

CogCAPTCHA30 Fingerprints AI Agents via Behavioral Analysis

ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 6.5 HN AI Security

Researchers have developed CogCAPTCHA30, a 30-task cognitive battery demonstrating that AI agents (GPT, Claude, Gemini) solve CAPTCHAs with statistically distinguishable behavioural patterns despite matching human accuracy. The study introduces a 'Process Turing Test' concept, showing output equivalence and process equivalence are uncorrelated — meaning AI agents can be detected not by what they answer, but by how they answer. This has direct implications for bot detection, anti-automation defences, and the arms race between AI-driven agents and human-verification systems.

Robinhood Prompt Injection Enables Autonomous Trade Attacks

Robinhood Prompt Injection Enables Autonomous Trade Attacks

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 7.2 HN AI Security

Robinhood has launched agentic trading and a virtual credit card that allow third-party AI agents to autonomously execute stock trades and payments on behalf of users via a Model Context Protocol (MCP) integration. This architecture introduces significant attack surface through prompt injection, excessive agency, and insecure plugin design risks inherent to LLM-driven autonomous financial action. The delegation of real financial authority to AI agents with limited human-in-the-loop controls represents a systemic risk to retail investors if agent pipelines are compromised or manipulated.

SQLite Blocks AI-Generated Code Contributions

SQLite Blocks AI-Generated Code Contributions

ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 6.2 Simon Willison

SQLite has formally prohibited agentic code contributions and strengthened its policy language, reflecting growing concern over AI-generated submissions overwhelming open source maintainers. The project was forced to create a separate bug forum after being flooded with AI-generated reports of inconsistent quality. This represents an emerging operational security challenge for critical infrastructure software projects targeted by autonomous AI coding agents.

Constraint Decay: LLM Code Agents Fail at Scale

Constraint Decay: LLM Code Agents Fail at Scale

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 7.2 HN AI Security

A systematic study of LLM agents performing backend code generation reveals a 'constraint decay' phenomenon where agents lose up to 30 assertion pass-rate points as structural requirements accumulate, approaching complete failure in some configurations. This fragility has direct security implications: production deployments relying on LLM-generated code may silently violate architectural constraints such as ORM patterns, database access controls, and API contracts. The findings expose a critical gap between functional correctness and structural safety in agentic coding systems.

SentinelOne Warns on Prompt Injection Risks in AI Agents

SentinelOne Warns on Prompt Injection Risks in AI Agents

ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 6.5 SentinelOne Blog

SentinelOne has published guidance on securing agentic AI systems, framing unverified trust in AI agents as a core enterprise risk. The piece promotes their Prompt Security product as a control layer for AI tools, agents, and pipelines deployed across the enterprise. While primarily a product-focused announcement, it highlights the genuine security challenge of blind trust in autonomous AI agents executing actions on behalf of users and systems.

Gemini Spark Prompt Injection Exposes Enterprise Gmail Data

Gemini Spark Prompt Injection Exposes Enterprise Gmail Data

ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 6.5 Simon Willison

Google's newly announced Gemini Spark personal AI agent, integrated with Gmail, Drive, Calendar, and other sensitive Google services, presents a significant prompt injection attack surface as it processes user data at scale. The article highlights that Google's published security mitigations — ephemeral VMs, Agent Gateway, and DLP policies — address infrastructure isolation but do not directly address the prompt injection vector inherent to LLM-powered agents processing untrusted content. Additionally, the transition from open-source Gemini CLI to a closed-source Antigravity CLI raises supply chain transparency concerns.

AI Agent Identity Sprawl Bypasses Enterprise IAM Systems

AI Agent Identity Sprawl Bypasses Enterprise IAM Systems

ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 6.2 Dark Reading

As AI agents proliferate across enterprise environments, their associated non-human identities are introducing governance and security gaps that traditional IAM frameworks were not designed to handle. New Omdia research highlights that AI agent identity management demands distinct budget allocations and security controls separate from conventional IAM programs. The failure to properly secure and govern these machine identities exposes organisations to credential abuse, privilege escalation, and lateral movement risks.

Microsoft RAMPART Tests AI Agents for Prompt Injection

Microsoft RAMPART Tests AI Agents for Prompt Injection

ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 7.2 The Hacker News

Microsoft has released two open-source tools, RAMPART and Clarity, aimed at embedding security testing into AI agent development workflows. RAMPART extends the existing PyRIT framework with a Pytest-native harness for running adversarial and safety tests against AI agents, explicitly covering cross-prompt injection, data exfiltration, and behavioural regression scenarios. Clarity operates as a pre-code design analysis tool, helping teams surface and challenge unsafe assumptions before an agentic system is built.

Agent Hijacking: Microsoft's Defense-in-Depth Framework

Agent Hijacking: Microsoft's Defense-in-Depth Framework

ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 7.2 Microsoft Security Blog

Microsoft's Security Blog introduces a layered defense-in-depth model specifically designed for autonomous AI agents, which now invoke tools, modify data, and trigger workflows with minimal human oversight. The framework identifies novel threat classes — including agent hijacking, intent breaking, and supply chain compromise — that are amplified by agentic autonomy. The guidance positions application-layer architecture, permissions, and governance as the most critical controls as agent autonomy scales.

Sweet Security Launches Sweet Attack Agentic AI Red Teaming

Sweet Security Launches Sweet Attack Agentic AI Red Teaming

ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 7.2 SecurityWeek

Sweet Security has launched 'Sweet Attack', a continuous agentic AI red teaming platform designed to counter the growing asymmetry between AI-assisted attackers and human defenders — a tipping point the industry has termed the 'Mythos Moment'. The platform differentiates itself by grounding frontier model reasoning in live runtime telemetry from each customer's own environment, including topology, identity paths, and unencrypted Layer 7 exposure, to identify genuinely exploitable attack chains rather than theoretical ones. The development signals a broader industry shift toward autonomous, environment-aware AI agents as a necessary component of modern security operations.

Microsoft MDASH Discovers 16 Windows RCE Flaws

Microsoft MDASH Discovers 16 Windows RCE Flaws

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 7.8 The Hacker News

Microsoft has disclosed MDASH, a multi-model agentic AI scanning system that autonomously discovered 16 vulnerabilities patched in May 2026's Patch Tuesday, including two critical RCE flaws. The system orchestrates over 100 specialised AI agents in a structured pipeline covering auditing, debating, and proof-of-exploitability stages. MDASH represents a significant shift in how AI is being deployed offensively and defensively within the vulnerability research lifecycle, with direct implications for how agentic AI systems are trusted, scoped, and governed.

OpenAI Daybreak Vulnerability Detection Enables LLM Jailbreak

OpenAI Daybreak Vulnerability Detection Enables LLM Jailbreak

ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 7.2 The Hacker News

OpenAI has launched Daybreak, an AI-powered cybersecurity platform combining GPT-5.5 variants and Codex Security to automate vulnerability detection, threat modelling, and patch validation for enterprise codebases. The initiative introduces a tiered model access structure — including a permissive 'GPT-5.5-Cyber' for red teaming — raising questions about dual-use risk and model misuse if access controls are circumvented. The rollout also contextualises a broader industry tension: AI is accelerating vulnerability discovery faster than defenders can remediate, contributing to triage fatigue and hallucinated bug reports.

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