#secureAI

Ironwood Logicironwoodlogic
2026-01-23

Equip a team of 50 with AI subscriptions and you're paying a permanent seat tax, with pricing and roadmap decisions controlled entirely by someone else. ironwoodlogic.com/articles/bey

Ironwood Logicironwoodlogic
2026-01-23

High-growth doesn't have to mean high-touch. Learn how a professional services firm reduced founder involvement by 65% while scaling operations. ironwoodlogic.com/case-studies

2026-01-20

A flaw in Google Gemini allows prompt injection to manipulate AI outputs β€” when instructions can be hijacked, trust in AI responses breaks fast. Guardrails matter. πŸ€–βš οΈ #PromptInjection #SecureAI

thehackernews.com/2026/01/goog

Ironwood Logicironwoodlogic
2026-01-20

Automation delivers the highest ROI when it eliminates repetitive tasks: data entry, follow-ups, status updates, report generation, scheduling. ironwoodlogic.com/articles/the

Ironwood Logicironwoodlogic
2026-01-18

Digital transformation fails not because of wrong technology, but sequencing failures. Order matters more than ambition. Build the foundation first. ironwoodlogic.com/articles/why

2026-01-16

Enterprise AI governance is becoming a board-level priority β€” without clear rules, scale amplifies risk faster than value. Control is now part of innovation. πŸ€–πŸ›οΈ #AIGovernance #SecureAI

helpnetsecurity.com/2026/01/16

2026-01-16

AI agents are becoming privileged users β€” accessing data, tools, and actions at scale. Without guardrails, autonomy turns into risk. Control must grow with capability. πŸ€–πŸ” #AIAgents #PrivilegeRisk #SecureAI

thehackernews.com/2026/01/ai-a

2026-01-08

New research shows risks emerge when AI systems interact with each other β€” complexity amplifies blind spots and unintended behavior. Securing AI isn’t just about models, but ecosystems. πŸ€–βš οΈ #SecureAI #SystemicRisk

helpnetsecurity.com/2026/01/07

2026-01-07

GenAI data violations are rising heading into 2026 β€” sensitive data leaks via prompts, training, and plugins are becoming a real business risk. AI needs guardrails, fast. πŸ€–πŸ”“ #SecureAI #DataProtection

helpnetsecurity.com/2026/01/07

2026-01-06

New research shows AI security governance gaps are growing fast β€” innovation is outpacing control, creating silent risk at scale. Governing AI is now a security priority. πŸ€–βš οΈ #AIGovernance #SecureAI

helpnetsecurity.com/2026/01/05

2026-01-05

The U.S. Army has announced a new AI and ML officer specialization to support its transition toward data-centric military operations.

For the security community, this signals increased emphasis on AI governance, secure model deployment, and protecting data pipelines and decision systems in critical environments.

As AI adoption expands across defense and government sectors, security architecture and operational safeguards will be just as important as capability gains.

What security controls should be non-negotiable for AI in defense contexts?

Source: forklog.com/en/us-army-to-esta

Follow TechNadu for unbiased cybersecurity and AI coverage.

#InfoSec #Cybersecurity #AI #MachineLearning #DefenseSystems #SecureAI #DataProtection #TechNadu

US Army to create AI officer specialization for data-centric transformation.
2025-12-24

AI security governance is moving to the forefront β€” without clear rules, innovation scales risk as fast as value. Trust in AI must be designed, not assumed. πŸ€–πŸ›οΈ #AIGovernance #SecureAI

helpnetsecurity.com/2025/12/24

Keerthana Purushothamkeepur@infosec.exchange
2025-12-24

Check out ˗ˏˋ β­’ lnkd.in/gE2wUqgc β­’ ΛŽΛŠΛ— to see my intro whilst you listen.

I'm thus re-naming this work as "CVE Keeper - Security at x+1; rethinking vulnerability management beyond CVSS & scanners". I must also thank @andrewpollock for reviewing several of my verbose drafts. 🫑

So, Security at x+1; rethinking vulnerability management beyond CVSS & scanners -

Most vulnerability tooling today is optimized for disclosure and alert volume, not for making correct decisions on real systems. CVEs arrive faster than teams can evaluate them, scores are generic, context arrives late, and we still struggle to answer the only question that matters: does this actually put my system at risk right now?

Over the last few years working close to CVE lifecycle automation, I’ve been designing an open architecture that treats vulnerability management as a continuous, system-specific reasoning problem rather than a static scoring task. The goal is to assess impact on the same day for 0-days using minimal upstream data, refine accuracy over time as context improves, reason across dependencies and compound vulnerabilities, and couple automation with explicit human verification instead of replacing it.

This work explores:

  1β€’ Same-day triage of newly disclosed and 0-day vulnerabilities
  2β€’ Dependency-aware and compound vulnerability impact assessment
  3β€’ Correlating classical CVSS with AI-specific threat vectors
  4β€’ Reducing operational noise, unnecessary reboots, and security burnout
  5β€’ Making high-quality vulnerability intelligence accessible beyond enterprise teams

The core belief is simple: most security failures come from misjudged impact, not missed vulnerabilities. Accuracy, context, and accountability matter more than volume.

I’m sharing this to invite feedback from folks working in CVE, OSV, vulnerability disclosure, AI security, infra, and systems research. Disagreement and critique are welcome. This problem affects everyone, and I don’t think incremental tooling alone will solve it.

P.S.

  • Super appreciate everyone that's spent time reviewing my drafts and reading all my essays lol. I owe you 🫢🏻
  • ... and GoogleLM. These slides would have taken me forever to make otherwise.

Take my CVE-data User Survey to allow me to tailor your needs into my design - lnkd.in/gcyvnZeE
See more at - lnkd.in/gGWQfBW5
lnkd.in/gE2wUqgc

#VulnerabilityManagement #Risk #ThreatModeling #CVE #CyberSecurity #Infosec #VulnerabilityManagement #ThreatIntelligence #ApplicationSecurity #SecurityOperations #ZeroDay #RiskManagement #DevSecOps #CVE #CVEAnalysis #VulnerabilityDisclosure #SecurityData #CVSS #VulnerabilityAssessment #PatchManagement #AI #AIML #AISecurity #MachineLearning #AIThreats #AIinSecurity #SecureAI #OSS #Rust #ZeroTrust #Security

linkedin.com/feed/update/urn:l

2025-12-23

AI-assisted pull requests are accelerating development β€” but also introducing new review and trust challenges. Speed is great, assurance is essential. πŸ€–πŸ§ͺ #SecureCoding #SecureAI

helpnetsecurity.com/2025/12/23

2025-12-10

AI agents are failing key safety tests β€” showing how easily autonomous systems can be misled or misaligned. Rigorous testing must mature as fast as the agents themselves. πŸ€–βš οΈ #SecureAI #AgentSecurity

helpnetsecurity.com/2025/12/09

2025-12-05

Interestingly, AI is now being used to police other AI β€” a recursive battle where models watch models. Oversight must evolve as fast as autonomy. πŸ€–πŸ” #SecureAI #AIGovernance

theregister.com/2025/12/05/an_

2025-12-03

ChatGPT suffers a global outage with conversations disappearing for users β€” a stark reminder of how dependent we’ve become on AI daily. Cloud smarts need cloud resilience. πŸ€–βš οΈ #SecureAI #Resilience

bleepingcomputer.com/news/arti

2025-12-02

The future of the SOC is human + AI β€” collaboration that boosts speed, precision, and resilience. Augmented analysts will outpace automated attackers. πŸ€πŸ€– #SOCEvolution #SecureAI

techcommunity.microsoft.com/bl

2025-11-25

ShadowRay 2.0 is hijacking AI clusters to build crypto-mining botnets β€” turning high-performance compute into high-profit crime. AI power cuts both ways. βš‘πŸ€– #SecureAI #CryptoBotnets

darkreading.com/cyber-risk/sha

2025-11-22

Perplexity’s new Comet browser and MCP API raise fresh security questions β€” when AI meets the web, the attack surface grows with every click. πŸŒπŸ€– #SecureAI #WebSecurity

helpnetsecurity.com/2025/11/20

Client Info

Server: https://mastodon.social
Version: 2025.07
Repository: https://github.com/cyevgeniy/lmst