Hackers Use AI for Exploit Development, Attack Automation TechTarget and Informa Tech’s Digital Business Combine.TechTarget and InformaTechTarget and Informa Tech’s Digital Business Combine.Together, we power an unparalleled network of 220+ online properties covering 10,000+ granular topics, serving an audience of 50+ million professionals with original, objective content from trusted sources. We help you gain critical insights and make more informed decisions across your business priorities.Dark Reading Resource LibraryBlack Hat NewsOmdia CybersecurityAdvertiseNewsletter Sign-UpNewsletter Sign-UpCybersecurity TopicsRelated TopicsApplication SecurityCybersecurity CareersCloud SecurityCyber RiskCyberattacks & Data BreachesCybersecurity AnalyticsCybersecurity OperationsData PrivacyEndpoint SecurityICS/OT SecurityIdentity & Access Mgmt SecurityInsider ThreatsIoTMobile SecurityPerimeterPhysical SecurityRemote WorkforceThreat IntelligenceVulnerabilities & ThreatsRecent in Cybersecurity TopicsСloud SecurityHackers Use AI for Exploit Development, Attack AutomationHackers Use AI for Exploit Development, Attack AutomationbyAlexander CulafiMay 11, 20264 Min ReadСloud SecurityAfter Replacing TeamPCP Malware, 'PCPJack' Steals Cloud SecretsAfter Replacing TeamPCP Malware, 'PCPJack' Steals Cloud SecretsbyNate NelsonMay 7, 20265 Min ReadWorld Related TopicsDR GlobalMiddle East & AfricaAsia PacificLatin AmericaSee AllThe EdgeDR TechnologyEventsRelated TopicsUpcoming EventsPodcastsWebinarsSEE ALLResourcesRelated TopicsResource LibraryNewslettersPodcastsReportsVideosWebinarsWhite Papers Partner PerspectivesDark Reading Resource LibraryСloud SecurityVulnerabilities & ThreatsThreat IntelligenceApplication SecurityNewsHackers Use AI for Exploit Development, Attack AutomationCyber adversaries have long used AI, but now attackers are using large language models to develop exploits and orchestrate complex attacks.Alexander Culafi,Senior News Writer,Dark ReadingMay 11, 20264 Min ReadSource: NicoElNino via Alamy Stock PhotoThreat actors are abusing AI tools in increasingly sophisticated ways, including exploit development and attack orchestration.Google today published new research tracking how adversaries leverage AI in their cyber operations. Since large language model (LLM) tools became widely available, threat actors have leveraged the technology in a wide range of ways, such as crafting phishing lures, coding malware, and conducting reconnaissance. They are also using AI, as Google detailed, for vulnerability research and exploit development.This research arrives as defenders contemplate how Anthropic's Claude Mythos model (and by extension Project Glasswing) will reshape the security ecosystem for years to come, as Anthropic claims Mythos is capable of finding critical zero-day vulnerabilities using natural language instruction. While this report doesn't claim threat actors are using anything like Mythos, Google's Threat Intelligence Group (GTIG) covers some of the cutting-edge ways attackers are using AI today.Related:After Replacing TeamPCP Malware, 'PCPJack' Steals Cloud SecretsNo Mythos Needed: Exploit Developed With AIFor example, GTIG said it identified a threat actor using a zero-day exploit the company believes was developed with AI – possibly the first of its kind. According to the report, the vulnerability is "implemented in a Python script that enables the user to bypass two-factor authentication (2FA) on a popular open-source, web-based system administration tool." The vulnerability requires valid user credentials to exploit.Although the threat actor was (or possibly is) planning to use the vulnerability on a massive scale, GTIG disclosed the bug to the appropriate vendor in the hopes of disrupting potential threat activity. "Although we do not believe Gemini was used, based on the structure and content of these exploits, we have high confidence that the actor likely leveraged an AI model to support the discovery and weaponization of this vulnerability," the report read. "For example, the script contains an abundance of educational docstrings, including a hallucinated CVSS score, and uses a structured, textbook Pythonic format highly characteristic of LLMs training data (e.g., detailed help menus and the clean _C ANSI color class)."Threat actors associated with China and North Korea have shown particular interest in using LLMs for vulnerability research. For example, GTIG has observed suspected Chinese actor UNC2814 prompting Gemini to take on the role of a network security researcher conducting vulnerability research into embedded devices like TP-Link firmware. The actor tells the AI they are "auditing it for pre-authentication remote code execution (RCE) vulnerabilities."Related:If AI's So Smart, Why Does It Keep Deleting Production Databases?North Korean actor Silent Chollima, also known as APT45, has been observed "sending thousands of repetitive prompts that recursively analyze different CVEs and validate PoC exploits." This, Google said, facilitates more robust exploit capabilities than the model would have otherwise. Threat actors have similarly trained on a specialized vulnerability repository known as "wooyun-legacy" with more than 85,000 real world vulnerability cases collected by the Chinese bug bounty platform WooYun between 2010 and 2016. Threat actors are also experimenting with agentic tools like OpenClaw and OneClaw to assist in vulnerability research. AI-Powered Attack OrchestrationBut one of the most striking use cases detailed in the report involved the use of AI in orchestrating attacks, as detailed with a malware family known as "PromptSpy." This is an Android backdoor first detailed by ESET, which abuses Gemini by prompting it to ensure the malicious app remains in the "recent apps" list. GTIG's analysis found that the backdoor used AI for other purposes, primarily "centered around navigating the Android user interface and autonomously interpreting real-time user activity for follow-on actions." For example, it can capture biometric data to replay authentication gestures to regain access to a compromised device. Related:TeamPCP Hits SAP Packages With 'Mini Shai-Hulud' AttackMoreover, threat actors are using agentic workflows to "operationalize autonomous frameworks to execute multi-stage security tasks." A China-nexus actor deployed agentic tools in an attack against a Japanese technology firm and an East Asian cybersecurity platform, according to the report. Agentic tools like Hextrike and Strix were used to maintain persistence across the attack surface and to both automate and validate vulnerabilities. "This combination of autonomous reconnaissance and automated verification suggests a transition toward AI-driven frameworks that can scale discovery activities with minimal human oversight," GTIG said.While slight and in limited cases, it is noteworthy to see threat actors move from heavily human-focused operations to campaigns where the AI takes more control. This mirrors the progression of AI in the defender space, where some organizations are moving away from human-in-the-loop thinking and toward human-on-the-loop, where agents are the primary AI orchestrators making moment-to-moment decisions and humans only intervene when necessary.Don't miss the latest Dark Reading Confidential podcast, How the Story of a USB Penetration Test Went Viral. Two decades ago Dark Reading posted its first blockbuster piece — a column by a pen tester who sprinkled rigged thumb drives around a credit union parking lot and let curious employees do the rest. This episode looks back at the history-making piece with its author, Steve Stasiukonis. Listen now!About the AuthorAlexander CulafiSenior News Writer, Dark ReadingAlex is an award-winning writer, journalist, and podcast host based in Boston. After cutting his teeth writing for independent gaming publications as a teenager, he graduated from Emerson College in 2016 with a Bachelor of Science in journalism. He has previously been published on VentureFizz, Search Security, Nintendo World Report, and elsewhere. In his spare time, Alex hosts the weekly Nintendo podcast Talk Nintendo Podcast and works on personal writing projects, including two previously self-published science fiction novels.See more from Alexander CulafiWant more Dark Reading stories in your Google search results?Add Us NowMore InsightsIndustry ReportsHow Enterprises Are Developing Secure ApplicationsInside RSAC 2026: security leaders reveal the risks redefining your defense strategyHow Enterprises Are Harnessing Emerging Technologies in CybersecurityDitch the Data Center: Understanding Flexible Cloud Infrastructure Security Management2025 State of MalwareAccess More ResearchWebinarsThe New Attack Surface: How Attackers Are Exploiting OAuth to Own Your Cloud WorkspacePrompt Injection Is Just the Start: Securing LLMs in AI SystemsAnatomy of a Data Breach: What to Do if it Happens to YouHow Well Can You See What's in Your Cloud?Implementing CTEM: Beyond Vulnerability ManagementMore WebinarsEditor's ChoiceThreat IntelligenceFrom Stuxnet to ChatGPT: 20 News Events That Shaped CyberFrom Stuxnet to ChatGPT: 20 News Events That Shaped CyberbyDark Reading Editorial TeamMay 6, 202631 Min ReadCyber RiskPhysical Cargo Theft Gets a Boost From CybercriminalsPhysical Cargo Theft Gets a Boost From CybercriminalsbyRobert LemosMay 4, 20265 Min ReadWant more Dark Reading stories in your Google search results?Keep up with the latest cybersecurity threats, newly discovered vulnerabilities, data breach information, and emerging trends. 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Hackers are increasingly utilizing artificial intelligence (AI), specifically large language models (LLMs), to develop exploits and orchestrate complex cyberattacks, according to a recent report by Google’s Threat Intelligence Group (GTIG). This shift marks a significant evolution in attack methodologies, moving beyond traditional human-driven approaches. The report details how threat actors are leveraging AI tools for various stages of the attack lifecycle, including vulnerability research, malware coding, and phishing lure creation.

Specifically, Google’s research highlights instances where threat actors, including those associated with China and North Korea, have prompted AI models—like Gemini—to simulate network security research, identifying pre-authentication remote code execution (RCE) vulnerabilities in embedded devices such as TP-Link firmware. Another observation involved the Chinese actor UNC2814 utilizing Gemini to act as a researcher, demonstrating an automated process for vulnerability analysis. The GTIG also identified a threat actor employing a zero-day exploit, potentially developed with AI, targeting a popular open-source web administration tool, bypassing two-factor authentication (2FA). The script’s structure and content, characterized by educational docstrings and a textbook Pythonic format, strongly suggest an LLM-driven approach.

Furthermore, the report describes the use of AI in attack orchestration, exemplified by the “PromptSpy” Android backdoor which abuses Gemini to ensure the malicious app remains in the “recent apps” list, automating user interface navigation and interpreting real-time activity for follow-on actions, including capturing biometric data for gesture replay and regained access. Evidence suggests that actors, like Hextrike and Strix, are utilizing agentic tools to maintain persistent access and automate verification processes. The GTIG observed a transition toward AI-driven frameworks with minimal human oversight, suggesting a move towards autonomous, scaleable reconnaissance activities.

The implications of this trend are significant for cybersecurity professionals, necessitating a reassessment of defenses. The report emphasizes a shift towards AI-powered attack orchestration, mirroring the progression of AI in the defensive space. The GTIG's analysis points toward a potential future where AI agents become the primary decision-makers, reducing reliance on human intervention. The use of “wooyun-legacy,” a large vulnerability repository, by threat actors further demonstrates the capability of AI to learn and adapt. This underscores the need for robust monitoring and detection capabilities capable of identifying and responding to AI-generated threats.