
Wiz relaunches Cyber Model Arena to score agent cyber tasks
Version 3.9 tests 59 agents on 327 challenges with a 1,000-second budget and deterministic grading.
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Version 3.9 tests 59 agents on 327 challenges with a 1,000-second budget and deterministic grading.

Autonomous AI systems enable continuous offensive security validation as environments change.

The author says AI-assisted teams logged 100-plus true positives on one app, versus 7 to 10 findings in a traditional engagement.

The six new tools cover XSS scanning, web crawling, port scanning, SDR and SMB share searches, while refreshed build scripts now support containerized builds via Docker or Podman.

Picus says agentic pentesting misses unreachable assets and flaws that lack safe exploits.
Open-source Decepticon red team agent links Claude Code and Codex to a LangGraph runtime for scoped attack-path testing.

Anthropic split Claude offensive-cyber access into three verification tiers matched to user trust and misuse risk.

Hadrian raised $40 million in Series B funding to expand its autonomous AI offensive security platform.

Security leaders argue AI-accelerated attacks require continuous, automated penetration testing and offensive security instead of annual compliance-driven assessments.

RemoteThreat, an offensive-security startup, wants teams to test attacker behavior after defenses fail.
Armadin raised a $255.5 million Series B to scale its AI offensive security platform.

RemoteThreat launched with $7 million pre-seed for an offensive operations platform combining C2, implants, initial access, and governed AI workflows.
Ex-IBM X-Force leaders launched RemoteThreat, a $7 million AI offensive-cyber startup for vetted enterprises and government.
A Hacker News thread links to a GitHub benchmark of uncensored offensive-security AI models.

Process parameter-poisoning injects code into process initialization structures, evading EDR tools that monitor standard Windows APIs.

Horizon3 offers NodeZero Federal, a FedRAMP High autonomous penetration-testing platform for federal agencies.
Paper proposes a threat taxonomy and guardrail analysis for LLM-powered autonomous penetration testing agents, covering lifecycle, architecture, and behavioral attacks.
Pre-registered ablation finds a model verifier stage in an LLM offensive-security agent suppresses findings; removing it eliminated suppression with precision tradeoff.
Researchers release PrivEscalate, a 531-scenario benchmark showing LLM agents' Linux privilege-escalation success varies by vulnerability class, plus PrivEscAgent, a domain-specialized agent that boosts success.
Studies honeypot-aware budget allocation for LLM attack agents, showing detector-guided policies let agents skip deception and compromise real hosts efficiently.
Researchers apply conformal prediction to offensive security, presenting initial findings on privacy-attacking machine learning and network traffic analysis.

Omdia's Theresa Lanowitz discusses surging offensive security investment and both the promise and risks of agentic AI in pentesting and red teaming.

Wiz's autonomous Red Agent found and exploited a GitHub Actions injection in a Copilot-assisted PR, reaching Snowflake's internal Jira without human help.

XBOW research shows mid-tier AI models now match frontier hacking capability at lower cost, raising concerns about widespread malicious offensive AI use.
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