All news with #ai red teaming tag

🔒 Prisma AIRS 2.0 presents a unified AI security platform that addresses the “AI black box” by combining AI Model Security and automated AI Red Teaming. It inventories models, inference datasets, applications and agents in real time, inspects model artifacts within CI/CD and model registries, and conducts continuous, context-aware adversarial testing. The platform integrates curated threat intelligence and governance mappings to deliver auditable risk scores and prioritized remediation guidance for enterprise teams.

🛡️ OpenAI Aardvark is an autonomous GPT-5-based agent that scans, analyzes and patches code by emulating a human security researcher. Rather than only flagging suspicious patterns, it maps repositories, builds contextual threat models, validates findings in sandboxes and proposes fixes via Codex, then rechecks changes to prevent regressions. OpenAI reports it found 92% of benchmark vulnerabilities and has already identified real issues in open-source projects, offering free coordinated scanning for selected non-commercial repositories.

🧬 Researchers used open-source AI to design variants of ricin and other toxic proteins, then converted those designs into DNA sequences and submitted them to commercial DNA-order screening tools. From 72 toxins and three AI packages they generated roughly 75,000 designs and found wide variation in how four screening programs flagged potential threats. Three of the packages were patched and improved after the test, but many AI-designed variants—often likely non-functional because of misfolding—exposed gaps in detection. The authors warn this imbalance could produce an arms race where design outpaces reliable screening.

🛡️ The UK AI Security Institute (AISI), Check Point and Lakera have launched b3, an open-source benchmark to assess and strengthen the security of backbone LLMs that power AI agents. b3 focuses on the specific LLM calls within agent workflows where malicious inputs can trigger harmful outputs, using 10 representative "threat snapshots" combined with a dataset of 19,433 adversarial attacks from Lakera’s Gandalf initiative. The benchmark surfaces vulnerabilities such as system prompt exfiltration, phishing link insertion, malicious code injection, denial-of-service and unauthorized tool calls, making LLM security more measurable, reproducible and comparable across models and applications.

🔧 Google details how its custom Axion Arm CPUs and a mix of automation and AI enabled large-scale migration from x86 to multi-architecture production across services such as YouTube, Gmail, and BigQuery. The team analyzed 38,156 commits (about 700K changed lines) and reports migrating more than 30,000 applications to Arm while keeping both Arm and x86 in production. Existing automation like Rosie, sanitizers, fuzzers, and the CHAMP rollout framework handled much of the work, while an LLM-driven agent called CogniPort fixed build and test failures, showing a 30% success rate on a 245-commit benchmark. Google plans to default new apps to multiarch and continue refining AI tools to address the remaining long tail.

🔒 Google Security Operations has been named a Leader in the 2025 Gartner Magic Quadrant for SIEM, recognized for both Ability to Execute and highest Completeness of Vision. The AI-driven platform leverages Gemini to automate data analysis, assist investigations with natural language, and orchestrate responses, combining curated detections, SOAR, and case-centric workflows. Customers report measurable outcomes — up to 240% ROI over three years, 50% faster MTTR, and 65% faster MTTI — driven by automation and an emerging agentic SOC vision.

🔍 Daniel Miessler argues that context determines the AI attack–defense balance: whoever holds the most accurate, actionable picture of a target gains the edge. He forecasts attackers will have the advantage for roughly 3–5 years as Red teams leverage public OSINT and reconnaissance while LLMs and SPQA-style architectures mature. Once models can ingest reliable internal company context at scale, defenders should regain the upper hand by prioritizing fixes and applying mitigations faster.

🔒 Microsoft Threat Intelligence stopped a credential phishing campaign that likely used AI-generated code to hide a payload inside an SVG file disguised as a PDF. Attackers sent self-addressed emails from a compromised small-business account, hiding real targets in the Bcc field and attaching a file named "23mb – PDF- 6 pages.svg." Embedded JavaScript decoded business-style obfuscation to redirect victims to a fake CAPTCHA and a fraudulent sign-in page, and Microsoft Defender for Office 365 blocked the campaign by flagging delivery patterns, suspicious domains and anomalous code behavior.

🔍 Intruder’s security team tested whether large language models can write Nuclei vulnerability templates and found one-shot LLM prompts often produced invalid or weak checks. Using an agentic approach with Cursor—indexing a curated repo and applying rules—yielded outputs much closer to engineer-written templates. The current workflow uses standard prompts and rules so engineers can focus on validation and deeper research while AI handles repetitive tasks.

⚠️ Ransomware attacks have accelerated to machine speed, often completing exfiltration and impact in minutes rather than days. Unit 42 research documents a dramatic decline in mean time to exfiltrate, driven by AI automation, initial access brokers and RaaS, which together enable highly targeted, fast-moving campaigns. Organizations now need AI-powered detection, automated containment and unified XDR visibility across endpoints, network and cloud to stop threats in real time. Human analysts remain vital but must operate alongside automated systems to focus on hunting and strategic response.

⚠️A new study, “Mind the Gap,” examines time-of-check to time-of-use (TOCTOU) flaws in LLM-enabled agents and introduces TOCTOU-Bench, a 66-task benchmark. The authors demonstrate practical attacks such as malicious configuration swaps and payload injection and evaluate defenses adapted from systems security. Their mitigations—prompt rewriting, state integrity monitoring, and tool-fusing—achieve up to 25% automated detection and materially reduce the attack window and executed vulnerabilities.

🛡️ Enterprises adopting agentic AI must update red‑teaming practices to address a rapidly expanding and interactive attack surface. The article summarizes the Cloud Security Alliance’s Agentic AI Red Teaming Guide and corroborating research that documents prompt injection, multi‑agent manipulation, and authorization hijacking as practical threats. It recommends five pragmatic steps—change attitude, continually test guardrails and governance, broaden red‑team skill sets, widen the solution space, and adopt modern tooling—and highlights open‑source and commercial tools such as AgentDojo and Agentgateway. The overall message: combine automated agents with human creativity, embed security in design, and treat agentic systems as sociotechnical operators rather than simple software.

⚠ Villager is an AI-native red-teaming framework from a shadowy Chinese developer, Cyberspike, that has been downloaded more than 10,000 times in roughly two months. The tool automates reconnaissance, exploitation, payload generation, and lateral movement into a single pipeline, integrating Kali toolsets with DeepSeek AI models and publishing on PyPI. Security firms warn the automation compresses days of skilled activity into minutes, creating dual-use risks for both legitimate testers and malicious actors and raising supply-chain and detection concerns.

🔒 HexStrike-AI, an open-source red‑teaming framework, is being adopted by malicious actors to rapidly weaponize newly disclosed Citrix NetScaler vulnerabilities such as CVE-2025-7775, CVE-2025-7776, and CVE-2025-8424. Check Point Research reports dark‑web chatter and evidence of automated exploitation chains that scan, exploit, and persist on vulnerable appliances. Defenders should prioritize immediate patching, threat intelligence, and AI-enabled detection to reduce shrinking n‑day windows.

🔒 CrowdStrike has acquired Spanish telemetry specialist Onum for $290 million, aiming to integrate its real-time pipeline and filtering technology into the Falcon Next‑Gen SIEM. The company says Onum’s pipeline will enable higher event throughput, reduce storage costs by about 50%, and cut ingest overhead while accelerating incident response. CrowdStrike frames the buy as a move toward an AI-native, agentic SOC.

🧠 Researchers at Carnegie Mellon University demonstrated that leading large language models (LLMs), by themselves, struggle to execute complex, multi-host cyber-attacks end-to-end, frequently wandering off-task or returning incorrect parameters. Their proposed solution, Incalmo, is a structured abstraction layer that constrains planning to a precise set of actions and validated parameters, substantially improving completion and coordination. The work highlights both enhanced offensive potential when LLMs are scaffolded and urgent defensive challenges for security teams.

🔒 Microsoft is relaunching Zero Day Quest with up to $5 million in total bounties for high-impact Cloud and AI security research. The Research Challenge runs 4 August–4 October 2025 and focuses on targeted scenarios across Azure, Copilot, Dynamics 365 and Power Platform, Identity, and M365. Eligible critical findings receive a +50% bounty multiplier, and top contributors may be invited to an exclusive live hacking event at Microsoft’s Redmond campus in Spring 2026. Participants will have access to training from the AI Red Team, MSRC, and product teams, and Microsoft will support transparent, responsible disclosure.

🛡️ Google outlines summer cybersecurity advances that combine agentic AI, platform improvements, and public-private partnerships to strengthen defenders. Big Sleep—an agent from DeepMind and Project Zero—has discovered multiple real-world vulnerabilities, most recently an SQLite flaw (CVE-2025-6965) informed by Google Threat Intelligence, helping prevent imminent exploitation. The company emphasizes safe deployment, human oversight, and standard disclosure while extending tools like Timesketch (now augmented with Sec‑Gemini agents) and showcasing internal systems such as FACADE at Black Hat and DEF CON collaborations.