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Offensive Security Investments Surge as AI Threats Increase
Omdia's Theresa Lanowitz discusses surging offensive security investment and both the promise and risks of agentic AI in pentesting and red teaming.
In a Dark Reading News Desk interview, Omdia analyst Theresa Lanowitz discusses why organizations are increasing offensive security spending as AI-driven threats grow. She weighs the potential and the risks of applying agentic AI to penetration testing, red teaming, and related offensive security practices.
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AI is Working in the SOC. So Why are Security Executives More Worried Than Ever?
An Omdia survey of 500 security leaders commissioned by Rapid7 reports 97% positive AI outcomes in the SOC despite heightened executive concerns.
Omdia, commissioned by Rapid7, surveyed 500 security professionals and found 97% reporting positive outcomes from AI in security operations. 98% said AI reduces alert fatigue and 95% said it helps address staffing shortages. Despite this consensus, the report highlights a growing confidence gap and elevated concerns among security executives about where operations are headed.
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AI Changed the Exposure Problem. Validation Needs to Change With It.
Picus Security argues vulnerability validation must combine exploitability, control validation, and agentic pentesting as AI accelerates disclosure volume.
Picus Security reports 35,853 CVEs were published in H1 2026, roughly 49% more than the prior year, while only 495 were catalogued as exploited in the wild and 116 were attacked on disclosure day. The vendor argues CVSS-based triage is inadequate and promotes combining exploitability validation, security control validation, and agentic pentesting into one program. The post also cites Anthropic data showing Mythos-class models surfaced 26,153 open-source vulnerability candidates with only 421 patched upstream, and promotes Picus's Validation Summit '26 on October 14-15.
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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.
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AI agents help compress ransomware intrusion to under 10 hours, raising stakes for CISOs
Unit 42 reports AI agents compressed a ransomware intrusion from weeks to under 10 hours, using 50+ MITRE ATT&CK techniques against an enterprise network.
Palo Alto Networks Unit 42 investigated a ransomware incident where AI agents moved through an enterprise network in under 10 hours, work that would have taken human operators roughly two weeks. The attacker entered via a public-facing API endpoint, used automated reconnaissance to map microservices, searched source-code repositories for credentials, and accessed a secrets-management system. They hijacked enterprise code workflows to exfiltrate cloud access keys, attempted Terraform backdoors (blocked by branch protections), and used stolen credentials to access the victim's own AI services as attack infrastructure. Over 50 MITRE ATT&CK techniques were observed; the actor confirmed using frontier AI models and agentic frameworks during negotiations.
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