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Gartner: 70% of SOCs will pilot AI agents. Only 15% will see results
Gartner predicts 70% of large SOCs will pilot AI agents by 2028, but only 15% will achieve measurable improvements.
A Gartner report by analysts Craig Lawson and Andrew Davies projects that by 2028, 70% of large SOCs will pilot AI agents for Tier 1 and Tier 2 operations, but only 15% will achieve measurable improvements without structured evaluation. Prophet Security's State of AI in Security Operations 2026 survey found 40% of security teams use AI daily and 56% are evaluating or piloting it. The report offers evaluation questions covering workload reduction, TDIR outcomes, vendor viability, analyst upskilling, and autonomy boundaries to counter AI washing in the market.
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What It Took to Reach 1 Billion Build Manifests
Chainguard doubled container build manifests to over 1 billion in six months, powered by Factory 2.0's agentic self-correcting rebuild system.
Chainguard reports growing from 500 million to over 1 billion container build manifests in six months, across more than 3,000 unique images and 675,000 image versions. Its Factory 2.0 system, built on the purpose-built Chainguard OS, uses an agentic reconciliation engine called DriftlessAF to decide when to rebuild across thousands of interdependent projects without human intervention. All artifacts ship with SLSA Level 3 provenance, Sigstore signatures, and full SBOMs.
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Drowning in CVEs and thirsty for answers? Try CTEM
Sponsored Register piece argues traditional vulnerability management cannot scale with CVE volume and promotes Continuous Threat Exposure Management via Horizon3's NodeZero.
The sponsored article cites surging CVE volumes, CVSS triage shortcomings, NVD backlog, and AI-driven discovery accelerating an asymmetric vulnerability cycle. It outlines Gartner's five CTEM steps - scoping, discovery, prioritization, validation, and mobilization - and describes how Horizon3's NodeZero automated pentesting validates exploitable attack paths with evidence. Horizon3 says NodeZero uses a deterministic machine learning expert system rather than general LLMs, limiting generative AI to scoped tasks via AWS Bedrock.
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Key Reasons Why Identity Fabric Matters in 2026
Identity sprawl and unowned machine identities leave enterprise access unobserved at runtime; identity fabrics aim to close the gap between policy intent and execution.
This sponsored explainer describes identity fabric as an architectural approach connecting identity providers, governance systems, applications, and infrastructure into one observable layer that compares designed access intent with runtime execution. It argues identity sprawl across SaaS, APIs, and cloud workloads, plus unmanaged non-human identities (service accounts, bots, workloads, API keys), leaves overprivileged, dormant, and unowned machine identities unmonitored. IdP-only monitoring misses application-layer attacks, and the piece advocates behavioral visibility and lifecycle governance for secrets and machine identities.
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Cybersecurity jobs available right now: May 19, 2026
Help Net Security's roundup lists cybersecurity openings across many countries, including CISO, threat intelligence, OT security, and AI security expert roles.
The roundup lists cybersecurity vacancies including CISO, SOC analyst, threat intelligence analyst, security engineer, OT security manager, and principal AI security expert positions. Employers include DataFence, Aldermore Bank, GDIT, Netcraft, Sonar, Sylvamo, MED-EL, and Crisis24 across the US, UK, India, Ireland, Australia, Austria, Canada, Germany, and the UAE. Nearly all listings were marked as no longer accepting applications at publication.
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The inconvenient truth about AI pentesting: someone has to check all the work
Survey of 158 practitioners shows AI pentesting floods teams with findings, creating 'validation debt' most teams cannot process.
The article argues AI pentesting creates 'validation debt': discovery scales far faster than teams' ability to verify AI-generated findings. In a survey of 158 practitioners, only 20.3% had workflows to triage more than 500 AI-generated candidates per engagement, while 29.7% called such volume unmanageable. One respondent spent two days validating 300 AI findings, of which 250 were duplicates, non-exploitable, or nonexistent. The author recommends capacity planning, ruthless deduplication, and risk-based prioritization before adopting AI pentesting tools.
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