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New Cryptographic Context Injection Attack Could Let Web Pages Steal Grok Chat Data
Adversa AI demonstrated 'Cryptographic Context Injection' making xAI's Grok leak chat history and session data to attacker-controlled servers via encrypted web payloads.
Adversa AI disclosed a technique where a web page carries an encrypted JSON object (PBKDF2 and AES-256-GCM) that Grok's code-execution runtime decrypts, letting attacker instructions bypass content classifiers and reach the model's context. The decrypted instructions direct Grok to embed the user's name, approximate location, subscription tier and ongoing conversation into a URL it fetches, exfiltrating the data without confirmation. Testing targeted grok.com running Grok 4.5 Fast on August 19, 2026, with a reported 40% success rate over 20 attempts since June; no CVE, patch, or in-the-wild exploitation is reported. A related demonstration reproduced Gemini 3 Flash system instructions via a fabricated Python traceback, while GPT-5 failed to parse the payload and Claude Sonnet 4.5 flagged it as prompt injection.
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You're deploying it wrong! TeamCity, Subversion & Web Deploy part 4: Continuous builds with TeamCity
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When AI Remembers Too Much
Unit 42 PoC shows indirect prompt injection can poison Amazon Bedrock Agent long-term memory, enabling silent exfiltration of conversation history across future sessions.
Palo Alto Networks Unit 42 published a proof of concept showing that indirect prompt injection can silently poison the long-term memory of Amazon Bedrock Agents when the memory feature is enabled. Malicious content on a webpage or document manipulates the agent's session summarization process, so injected instructions persist across sessions and are added to later orchestration prompts, silently exfiltrating user conversation history. The issue is not a vulnerability in the Amazon Bedrock platform but an illustration of the broader unsolved LLM prompt-injection challenge. Amazon reviewed the research and stated that Bedrock Guardrails with the prompt-attack policy provides effective mitigation.
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Amazon Kiro Prompt Injection Can Exfiltrate Sensitive Data Through Kiro Powers
Mindgard found a prompt injection flaw in Amazon Kiro IDE letting attacker-controlled workspace files exfiltrate sensitive local data; fixed in version 0.8.140.
Mindgard disclosed a prompt injection flaw in Amazon Kiro, an agentic AI IDE, that lets attacker-controlled repository content steer the agent into exfiltrating sensitive workspace data through Kiro Powers, which bundles MCP server configurations, POWER.md steering files, hooks, and contextual knowledge. Exploitation requires the user to open a malicious project via a workspace file and send any message to the agent; difficulty is rated low and it works in both trusted and untrusted workspaces. Amazon fixed the issue in Kiro IDE 0.8.140; the flaw has no CVE identifier and follows earlier Kiro bugs including CVE-2026-10591, plus related prompt-injection and code-execution issues in Codex CLI, Cursor, Gemini CLI, Copilot CLI, and Claude Code.
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GPT4Free Privacy Risks Expose AI Prompts to Third-Party Servers and Hidden Logs
Gen Digital researchers found GPT4Free's hosted chat routes prompts through third-party servers, mislabels models, and logs IPs and conversations for up to 30 days.
Gen Digital researchers tested the GPT4Free (G4F) hosted chat at g4f.dev and found requests routed through intermediary endpoints such as an OpenAI-compatible g4f.space endpoint before reaching providers like Google Gemini, sometimes returning different model identifiers such as gemini-3-flash-preview. Provider code referenced JSON files listing over 200 externally reachable Ollama and llama.cpp endpoints whose ownership and authorization were undisclosed. Code paths reportedly retain usage logs for 14 days (IP addresses, approximate geolocation, provider, model, conversation data) and error logs for 30 days, while Privacy Policy and Terms of Service links redirected to a member area instead of the documents.
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One Extension Could Hijack AI Assistants Across Chrome, Comet, Edge, Opera Neon and Claude
Researchers showed a single browser extension could hijack AI agents in Chrome, Edge, Comet, Opera Neon and Claude in Chrome, earning $20,000 in bounties.
Forever Security demonstrated that a browser extension with two common permissions could seize the trusted page controlling built-in AI assistants in five Chromium-based products and drive the agent, read local files, or access the camera. Chrome's flaw was fixed as CVE-2026-0628 (CVSS 8.8) in Chrome 143.0.7499.192, and Microsoft fixed CVE-2026-55945 (CVSS 4.2) in Edge 150.0.4078.48. Perplexity Comet was the worst case: a hijacked agent could read any file, leak browsing history, take screenshots, and act as the user via an unsecured test subdomain. All attacks require a malicious extension already installed; no in-the-wild exploitation or KEV listing was reported as of September 16, 2026.
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How MCP Servers Can Expose Enterprise Secrets
MCP servers holding AI agent credentials risk secret exposure via plaintext configs, credential sprawl, prompt injection, and over-permissioning; mitigations include centralization and least privilege.
The article examines how Model Context Protocol servers, which hold API keys, tokens, and service-account credentials for AI agents, can leak enterprise secrets. Documented exposure paths include plaintext credentials in config files, ungoverned credential sprawl, prompt injection, over-permissioning, and untrusted third-party servers. It cites CVE-2025-6514 in mcp-remote (400,000+ downloads), where a malicious server triggered OS command injection leading to remote code execution. Recommended mitigations include centralized secret stores, short-lived auto-rotated credentials, least privilege, and human approval for sensitive actions.
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Securing Claude Code: The New Compliance API, Local Visibility, and Identity Governance
Anthropic's new Compliance API endpoints expose Claude Code local session transcripts, highlighting governance gaps for endpoint AI agents.
Anthropic added local session transcript endpoints to its Compliance API on August 11, 2026, giving security teams visibility into prompts, bash commands, file operations, and MCP commands run by Claude Code harnesses on endpoints. The article argues local harnesses break the classic shared-responsibility model, citing Token Security data that 68.6% of discovered AI agents run on endpoints, and a Cloud Security Alliance survey of 418 IT and security professionals in which 82% found an unknown agent within the past year. It outlines three governance layers: Anthropic managed settings as a policy baseline, the Compliance API for cloud-visible transcripts, and endpoint telemetry to connect agent activity to identity, credentials, and permissions.
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⚡ Weekly Recap: Telecom Sleeper Cells, LLM Jailbreaks, Apple Forces U.K. Age Checks and More
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Who's governing your AI? A trust framework for enterprise agents and models
DigiCert pitches AI Trust framework using PKI, DNS policy records and workload identity to govern shadow AI agents across enterprises.
The Register-sponsored piece outlines DigiCert's AI Trust framework for governing AI agents, built on PKI, DNS, and attestation, citing IBM's 2026 Cost of a Data Breach report that 68% of organizations lack AI governance or shadow AI detection. The approach treats agent identity as workload identity aligned with IETF WIMSE, NIST CSF 2.0, and SPIFFE/SPIRE, using short-lived credentials instead of static API keys. DigiCert also proposes DMARC-style DNS agent policy records and an AI Agent Passport cryptographically binding agent identity to approved operations, with a unified kill switch.
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One in four MCP servers opens AI agent security to code execution risk
Noma Security whitepaper finds most popular AI Skills and many MCP servers carry high-risk capabilities, with state changes most prevalent.
Noma Security analyzed hundreds of popular MCP servers and Skills across eight risk categories, finding most widely used Skills carry at least one risky characteristic and a typical enterprise runs well over a hundred high-risk agent tools, with arbitrary code execution common across MCP servers. The most prevalent risk is the ability to change state or data, and named toxic combinations include ContextCrush data leakage, ForcedLeak via poisoned Salesforce CRM records, DockerDash supply-chain compromise, the Replit production database deletion, and the hijacked Amazon Q VS Code extension. Building on OWASP LLM06:2025, the paper proposes the No Excessive CAP framework of capabilities, autonomy, and permissions, recommending allowlisting, MCP version pinning, approval gates on irreversible actions, and user-scoped expiring credentials.
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