Search: “Compliance API”

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DomainAll Cyber AIWindow24h 3d 7d 30d AllIn the wild Important only Show duplicates

CategoryAll Vulnerability 370 Policy & legal 248 Data breach 169 AI tools & infra 131 Ransomware 127 Phishing & fraud 66 Exploit / PoC 65 AI safety & security 53 Malware 48 Tools 26 Industry 22 Threat actor 21 AI industry 16 Model release 14

SeverityAll critical 599 high 194 medium 221 low 173 info 221

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.

The Hacker NewsAug 31, 11:31 UTC · 17d agoAI safety & security1

Malicious MCP Servers Can Split Instructions to Make AI Coding Agents Exfiltrate Secrets

ASSET Research Group's GhostSplice technique splits malicious instructions across MCP channels, tricking AI coding agents into exfiltrating SSH keys, source code, and secrets.

ASSET Research Group disclosed GhostSplice, a prompt-injection technique in which a malicious Model Context Protocol (MCP) server splits an exfiltration instruction across a tool description and a tool result so no single fragment appears harmful. In the reference implementation, a benign-looking integrity_checker tool with fields alpha through delta is later paired with a project-scan result mapping those fields to .ssh/id_rsa, proprietary source, customers.csv, and .env. Tests across eleven API-tested models showed average compliance rising from 42% to 82% when instructions were split in two, with GPT-4o, Gemini 2.0 Flash, and Llama 3.3 70B going from 0% to 100%. The findings come from controlled lab tests, not a reported real-world intrusion, and no CVE identifiers had been assigned as of August 10, 2026.

The Hacker NewsAug 11, 10:24 UTC · Aug 11, 2026AI safety & security1

AI deployments are stretching enterprise security to its limits

NetFoundry survey finds AI deployments will expand enterprise attack surfaces by 14%, with 90% of leaders worried about unapproved employee AI use.

NetFoundry's 2026 State of Secure AI Access survey found CISOs and CTOs expect AI deployments to grow attack surfaces by an average 14% within a year, with 90% concerned about employees using unapproved AI tools. Only 15% expressed high confidence that existing tools protect AI deployments, while non-human identities, static credentials and internet-facing APIs drive risk, and vulnerability exploitation now accounts for about 31% of breaches. Security reviews and network changes add an average eight days to AI deployments, and the median time to patch known exploited vulnerabilities has risen to 43 days.

Help Net SecurityAug 12, 00:00 UTC · Aug 12, 2026AI safety & security

10 most critical LLM vulnerabilities

OWASP updated its Top 10 LLM application vulnerabilities, ranking prompt injection first and elevating excessive agency to third amid agentic adoption.

OWASP refreshed its Top 10 list of critical vulnerabilities in LLM applications, for the first time incorporating real-world incident data alongside expert voting. Prompt injection and sensitive information disclosure remain first and second, while excessive agency jumped from sixth to third as agentic systems that call APIs and execute code proliferate. Unbounded consumption of AI resources rose in prominence, while improper output handling dropped to the bottom as output sanitization becomes widespread. The list includes remediation guidance such as strict output schemas, human-in-the-loop approvals, and least-privilege credentials held in application code.

CSO OnlineSep 10, 08:25 UTC · 7d agoAI safety & security

How to Secure Enterprise AI: From Adoption to Incident Readiness

Sygnia-backed guidance urges a lifecycle approach to enterprise AI security, citing survey data that AI adoption is outpacing governance and incident readiness.

The Hacker News published Sygnia-sponsored guidance on securing enterprise AI across its lifecycle, from use-case definition and vendor selection to deployment and incident readiness. It cites Sygnia's 2026 CISO survey of 600 senior leaders: 63% expect AI fully embedded by 2027, 73% say their organization would not be fully ready for a significant cyberattack, and 67% of executives believe unapproved AI tools already caused a breach. The piece highlights shadow AI, ad hoc integrations, and over-permissioned AI agents as key attack surface risks, noting only 38% of organizations report a comprehensive AI policy.

The Hacker NewsSep 2, 11:30 UTC · 15d agoAI safety & security

What 90 days and a small budget can buy in AI agent security

Versa Field CISO details hidden costs of self-hosting open-weight models and a 90-day AI agent security plan of inventory, blast-radius reduction and testing.

In a Help Net Security interview, Prasad Tharippala, Field CISO at Versa, argues running open-weight models in-house improves control but shifts hardening, patching, access control, monitoring and incident response onto the buyer, with underestimated costs in GPU infrastructure, licensing review, EU AI Act compliance and scarce AI/ML security skills. On red-teaming AI agents, he recommends testing prompt injection, indirect injection, excessive permissions, data leakage, memory and RAG poisoning, malicious tool outputs, cross-agent trust abuse and infrastructure attack paths, mapped to OWASP agentic guidance and MITRE ATLAS. He highlights the handoff between chained agents as a major risk zone and stresses exercising human approval, shutdown and rollback controls under test conditions. For teams with 90 days and small budgets, he ranks inventory, blast radius reduction and ongoing testing as the priority order.

Help Net SecurityAug 28, 00:00 UTC · 20d agoAI safety & security

AI supply chain risk is showing up in developer workflows first

Zentera Systems CEO says AI supply chain attacks currently hit developer workflows first, advising segmentation over tooling and citing the Phantom Raven campaign.

In an interview, Zentera Systems CEO Dr. Jaushin Lee argues that most active AI supply chain incidents target developer workflows and open-source package repositories, while poisoned model weights, compromised MCP servers, and poisoned vector stores remain largely in research and demos. He cites the active 'Phantom Raven' campaign, where attackers register AI-hallucinated package names in public repositories with malicious payloads that silently infect vibe-coding build pipelines. He recommends software-defined segmentation, semiconductor-style project enclaves with egress controls, and warns that self-hosting models without agent sandboxing leaves exposure unchanged.

Help Net SecurityAug 25, 00:00 UTC · 23d agoAI safety & security

The Outsized Shadow: Why 5% of AI Users Are Your Biggest Security Risk

Akamai's 2026 Enterprise AI Usage report finds the top 5% of AI power users create outsized shadow AI, data leakage, and agent security risks.

Akamai's State of the Internet: Enterprise AI Usage Risk Report 2026, based on real-world usage telemetry, finds the top 5% of enterprise AI power users interact with AI models at 12 times the rate of the bottom 50% of the workforce. 47.11% of enterprise AI conversations occur through personal identities rather than corporate-managed accounts, and 14.4% run through corporate email addresses tied to personal freemium subscriptions. 17.7% of employees at midsize enterprises use AI browser or IDE extensions, of which 16.31% contain known CVE vulnerabilities and nearly 75% request high or critical permissions. The report also describes emerging attack vectors including Vibe Hacking, CursorJacking, and CometJacking indirect prompt injection.

The Hacker NewsAug 24, 11:30 UTC · 24d agoAI safety & security1

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.

The Hacker NewsAug 17, 11:58 UTC · Aug 17, 2026AI safety & security CVE-2025-6514

Securing AI agents: Key controls and best practices

Security experts warn AI agents with employee-level privileges outpace human access controls and advise layered enforcement, sandboxing, and approval gates.

CSO reports that enterprises granting AI agents credentials, tools, and network access face risks that human-focused identity controls cannot contain, including machine-speed action chaining and sub-agent spawning. Experts from Strike Graph, Veracode, Delinea, and XBOW recommend treating agents as privileged insiders with hard technical boundaries: egress proxies with allowlists, short-lived brokered tokens, separated read/write rights, and approval for high-risk actions. XBOW describes a layered architecture with a guardian model reviewing agent actions and per-agent audit files. OWASP guidance on excessive agency urges limiting agent functions, permissions, and autonomy with authorization enforced downstream.

CSO OnlineSep 8, 08:25 UTC · 9d agoAI safety & security