All news with #autonomous agents tag

Smashing Security Ep 444: Honest Breach and Hotel Phish

📰 In episode 444 of the Smashing Security podcast Graham Cluley and guest Tricia Howard examine a refreshingly candid breach response where a company apologised and redirected a ransom payment to cybersecurity research, illustrating how legacy systems can still magnify risk. They unpack a sophisticated hotel-booking malware campaign that abuses trust in apps and CAPTCHAs to deliver PureRAT. The hosts also discuss the rise of autonomous pen testing, AI-turbocharged cybercrime, and practical questions CISOs should be asking on Monday morning, with a featured interview featuring Snehal Antani from Horizon3.ai.

Adversarial AI Bots vs Autonomous Threat Hunters Outlook

🤖 AI-driven adversarial bots are rapidly amplifying attackers' capabilities, enabling autonomous pen testing and large-scale credential abuse that many organizations aren't prepared to detect or remediate. Tools like XBOW and Hexstrike-AI demonstrate how agentic systems can discover zero-days and coordinate complex operations at scale. Defenders must adopt continuous, context-rich approaches such as digital twins for real-time threat modeling rather than relying on incremental automation.

Four Steps for Startups to Build Multi-Agent Systems

🤖 This post outlines a concise four-step framework for startups to design and deploy multi-agent systems, illustrated through a Sales Intelligence Agent example. It recommends choosing between pre-built, partner, or custom agents and describes using Google's Agent Development Kit (ADK) for code-first control. The guide covers hybrid architectures, tool-based state isolation, secure data access, and a three-step deployment blueprint to run agents on Vertex AI Agent Engine and Cloud Run.

When to Use Sub-Agents Versus Agents as Tools for ADK

🧭 This post explains when to use sub-agents versus packaging agents as tools when building multi-agent systems with Google's Agent Development Kit (ADK). It contrasts agents-as-tools — encapsulated, stateless specialists invoked like deterministic function calls — with sub-agents, which are stateful, context-aware delegates that manage multi-step workflows. The guidance highlights trade-offs across task complexity, context sharing, reusability, and autonomy, and illustrates the patterns with data-agent and travel-planner examples to help architects choose efficient, scalable designs.

Agent Factory Recap: Build AI Apps in Minutes with Google

🤖 This recap of The Agent Factory features Logan Kilpatrick from Google DeepMind demonstrating vibe coding in Google AI Studio, a Build workflow that turns a natural-language app idea into a live prototype in under a minute. Live demos included a virtual food photographer, grounding with Google Maps, the AI Studio Gallery, and a speech-driven "Yap to App" pair programmer. The episode also surveyed agent ecosystem updates—Veo 3.1, Anthropic Skills, and Gemini improvements—and highlighted the shift from models to action-capable systems.

OpenAI Aardvark: Autonomous GPT-5 Agent for Code Security

🛡️ 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.

OpenAI Unveils Aardvark: GPT-5 Agent for Code Security

🔍 OpenAI has introduced Aardvark, an agentic security researcher powered by GPT-5 that autonomously scans source code repositories to identify vulnerabilities, assess exploitability, and propose targeted patches that can be reviewed by humans. Embedded in development pipelines, the agent monitors commits and incoming changes continuously, prioritizes threats by severity and likely impact, and attempts controlled exploit verification in sandboxed environments. Using OpenAI Codex for patch generation, Aardvark is in private beta and has already contributed to the discovery of multiple CVEs in open-source projects.

Agentic AI: Reset, Business Use Cases, Tools & Lessons

🤖 Agentic AI burst into prominence with promises of streamlining operations and accelerating productivity. This Special Report assesses what's practical versus hype, examining the current state of agentic AI, the primary deployment challenges organizations face, and practical lessons from real-world success stories. It highlights business processes suited to agentic agents, criteria for evaluating development tools, and how LinkedIn built a platform. The report also outlines near-term expectations and adoption risks.

Master Multitasking with the Jules Extension for Gemini CLI

🤖 The new Jules extension for Gemini CLI lets developers delegate routine engineering tasks—like bug fixes, dependency updates, and vulnerability patches—to an autonomous background agent. Jules runs asynchronously and can work on multiple GitHub issues in parallel, preparing fixes in isolated environments for review. It also composes with other extensions to automate security remediation, crash investigation, and unit test creation, returning ready-to-review branches so you can stay focused on higher-value work.

GitHub Agent HQ: Native, Governed AI Agents in Flow

🤖 GitHub announced Agent HQ, a unified platform that makes coding agents native to the GitHub workflow. Over the coming months, partner agents from OpenAI, Anthropic, Google, Cognition, and xAI will become available as part of paid Copilot subscriptions. The release introduces a cross‑surface mission control, VS Code planning and customizable AGENTS.md files, and an enterprise control plane with governance, metrics, and code‑quality tooling to manage agent-driven work.

Cortex AgentiX: Agentic AI Platform for Autonomous SOC

🤖 Palo Alto Networks introduces Cortex AgentiX, an agentic AI platform designed to build, deploy and govern autonomous security and IT agents. The vendor says AgentiX extends the Cortex foundation and leverages 1.2 billion playbook executions to deliver end-to-end agentic workflows and drive up to a 98% reduction in Mean Time to Respond with 75% less manual work. It ships with prebuilt agents for threat intelligence, email, endpoint, network, cloud and IT, and highlights full transparency, role-based controls and human-in-the-loop approvals. AgentiX is embedded in Cortex XSIAM and Cortex Cloud today; a standalone platform and Cortex XDR integration are slated for early 2026.

AI 2030: The Coming Era of Autonomous Cybercrime Threats

🔒 Organizations worldwide are rapidly adopting AI across enterprises, delivering efficiency gains while introducing new security risks. Cybersecurity is at a turning point where AI fights AI, and today's phishing and deepfakes are precursors to autonomous, self‑optimizing AI threat actors that can plan, execute, and refine attacks with minimal human oversight. In September 2025, Check Point Research found that 1 in 54 GenAI prompts from enterprise networks posed a high risk of sensitive-data exposure, underscoring the urgent need to harden defenses and govern model use.

Google Migrates ISAs with AI and Automation at Scale

🔧 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.

Agentic AI and the OODA Loop: The Integrity Problem

🛡️ Bruce Schneier and Barath Raghavan argue that agentic AIs run repeated OODA loops—Observe, Orient, Decide, Act—over web-scale, adversarial inputs, and that current architectures lack the integrity controls to handle untrusted observations. They show how prompt injection, dataset poisoning, stateful cache contamination, and tool-call vectors (e.g., MCP) let attackers embed malicious control into ordinary inputs. The essay warns that fixing hallucinations is insufficient: we need architectural integrity—semantic verification, privilege separation, and new trust boundaries—rather than surface patches.

CISOs Brace for an Escalating AI-versus-AI Cyber Fight

🔐AI-enabled attacks are rapidly shifting the threat landscape, with cybercriminals using deepfakes, automated phishing, and AI-generated malware to scale operations. According to Foundry's 2025 Security Priorities Study and CSO reporting, autonomous agents can execute full attack chains at machine speed, forcing defenders to adopt AI as a copilot backed by rigorous human oversight. Organizations are prioritizing human risk, verification protocols, and training to counter increasingly convincing AI-driven social engineering.

Google Cloud Marketplace for Enterprise and AI Agents

🤖 Google Cloud Marketplace offers a vetted path for organizations to deploy, buy, or build AI agents that integrate with Gemini Enterprise, simplifying procurement and deployment. Listings are pre-validated for A2A integration and allow consolidated billing, while administrators can enforce governance using IAM and Private Marketplace controls. For partners, the Marketplace provides global reach, co-selling, and flexible monetization (subscription, usage-based, private offers, outcome-based) plus automated provisioning via Pub/Sub and the Cloud Commerce Partner Procurement API.

Autonomous AI Hacking and the Future of Cybersecurity

⚠️AI agents are now autonomously conducting cyberattacks, chaining reconnaissance, exploitation, persistence, and data theft at machine speed and scale. In 2025 public demonstrations—from XBOW’s mass submissions on HackerOne in June, to DARPA teams and Google’s Big Sleep in August—along with operational reports from Ukraine’s CERT and vendors, show these systems rapidly find and weaponize new flaws. Criminals have operationalized LLM-driven malware and ransomware, while tools like HexStrike‑AI, Deepseek, and Villager make automated attack chains broadly available. Defenders can also leverage AI to accelerate vulnerability research and operationalize VulnOps, continuous discovery/continuous repair, and self‑healing networks, but doing so raises serious questions about patch correctness, liability, compatibility, and vendor relationships.

Salesforce launches AI security and compliance agents

🔒 Salesforce introduced two AI agents on its Agentforce platform that monitor security activity and streamline compliance workflows for the Security Center and Privacy Center. The security agent analyzes event logs to detect anomalous behavior, accelerates investigations by assembling context and remediation plans, and can autonomously freeze or isolate suspicious accounts when authorized. The privacy agent maps metadata and policies against frameworks like GDPR and CCPA, surfaces exposures, and can reclassify or apply erasure policies to reduce compliance risk.

Autonomous AI Hacking: How Agents Will Reshape Cybersecurity

⚠️ AI agents are increasingly automating cyberattacks, performing reconnaissance, exploitation, and data theft at machine speed and scale. In 2023 examples include XBOW's mass vulnerability reports, DARPA teams finding dozens of flaws in hours, and reports of adversaries using Claude and HexStrike-AI to orchestrate ransomware and persistent intrusions. This shift threatens accelerated attacks beyond traditional patch cycles while presenting new defensive opportunities such as AI-assisted vulnerability discovery, VulnOps, and even self-healing networks.

DeepMind's CodeMender: AI Agent to Fix Code Vulnerabilities

🔧 Google DeepMind has unveiled CodeMender, an autonomous agent built on Gemini Deep Think models that detects, debugs and patches complex software vulnerabilities. In the last six months it produced and submitted 72 security patches to open-source projects, including codebases up to 4.5 million lines. CodeMender pairs large-model reasoning with advanced program-analysis tooling — static and dynamic analysis, differential testing, fuzzing and SMT solvers — and a multi-agent critique process to validate fixes and avoid regressions. DeepMind says all patches are currently human-reviewed and it plans to expand maintainer outreach, release the tool to developers, and publish technical findings.