Combating AI Hallucinations in Digital Forensics

This may be an unpopular opinion, but the industry is quickly trending toward cyberattacks and large-scale breaches being a matter of "when," not "if." Another not-so-fun-fact: if your SOC is still relying primarily on manual investigation workflows and static detections, you are falling behind. AI is significantly compressing the timeline defenders used to be able to rely on. We've gone from having months to respond to newly disclosed vulnerabilities to, increasingly, only days before active exploitation begins. Attackers are using AI to accelerate every part of the process, and the gap between disclosure and weaponization continues to shrink. At some point, preventing every intrusion simply becomes unrealistic. What is becoming critically important is how quickly you can detect abnormal behavior, understand scope, and contain an activity before an attacker can establish persistence or move laterally. This is where UEBA and agentic AI become important. Traditional detections alone are not keeping pace with AI-accelerated attacks and rapidly weaponized vulnerabilities. Your security team needs a system that can correlate activity, identify anomalous behavior, reduce MTTD and MTTR, and minimize blast radius as much as possible.

Following a similar move by the UK Government, the Australian Government has issued an open letter to businesses regarding AI-related cyber risks. The guidance explicitly calls on Boards to elevate their AI literacy to ensure robust governance. Specifically, Boards are expected to: - Maintain AI Literacy: Develop the technical fluency required to set strategic direction and provide meaningful oversight. - Align AI Strategy with Risk: Oversee an AI roadmap that fits the organization's risk appetite, backed by rigorous monitoring and reporting. - Ensure Operational Resilience: Establish clear triggers for intervention, including for third-party dependencies, to take timely action if AI systems deviate from expected performance. #AIRisk #Governance #BoardofDirectors #AI https://lnkd.in/gESY-Hzm

The Five Eyes just published joint guidance on agentic AI security. Six national cyber agencies signed off: CISA, NSA, ASD's ACSC, NCSC-UK, the Canadian Centre for Cyber Security, and NCSC-NZ. The behaviors they describe aren't theoretical. Bridgewell Advisory has been documenting them across commercial and DoD AI environments for over a year: Goal misalignment. Specification gaming. Sycophantic and deceptive behavior. Agents that change behavior under evaluation. Strategic deception, where an agent hides capabilities to avoid being shut down. Cascading failures across components. Accountability gaps where no one can trace who decided what. The Five Eyes conclusion: governance, accountability, monitoring, and human oversight are essential prerequisites, not optional safeguards. That's the problem A3T™ solves. A3T is a governance overlay that constrains how AI systems respond. No model change, no retraining. It enforces truth before completion, silence over fabrication, structure over prompting, human authority over output. The other half is Human Training. Cross-substrate testing across six commercial platforms and two DoD environments documented 19 common failure modes. A3T governance alone resolves 5. A3T plus a trained human operator resolves 11 and mitigates the remaining 8. Humans and AI. Better Together. That's not a tagline. That's what the data shows. And now what the Five Eyes have validated. Read the joint guidance: https://lnkd.in/e4cvs-iz A3T™ and the Behavioral Governance Criteria for AI Acquisition: https://aiasateam.com #AIGovernance #Cybersecurity #DefenseAcquisition #AgenticAI

A single phishing email led to stolen BIOS firmware, persistent reverse shells, and full compromise of a privileged engineering account. I recently completed the TryHackMe AI Forensics room and documented the full investigation process. The attack chain started with a fake invoice spreadsheet. It ended with proprietary source code staged in volatile memory and prepared for exfiltration. What made this investigation interesting was the use of ML-assisted DFIR tooling during analysis. The models helped surface suspicious logins, hidden payloads, and anomalous files within minutes. They also produced false positives that could have easily misled the investigation without human validation. One detail stood out more than anything else. The attacker never used an exploit for privilege escalation. They used legitimate permissions and quietly modified an SSH authorized_keys file to gain persistent elevated access. No crash. No malware pop-up. No obvious alert. Just one command buried in shell history. The biggest takeaway for me was simple. AI is a force multiplier in DFIR. Not a replacement for analyst judgment. I broke down the full attack chain, tooling, persistence methods, and forensic findings here: https://lnkd.in/edJ94u4u Cc: TryHackMe Confidence Staveley #DFIR #AISECURITY #AIFORENSICS

In partnership with The London Foundation for Banking & Finance (LFBF), we have launched a new report on AI risk in financial services. ‘It’s still not magic' explores the opportunities generative AI presents, alongside the growing challenges around governance, trust and control. The research found that: - 70% said AI risks are among the greatest facing the sector over the next five years. - 75% said those risks have increased substantially since generative AI became widely available. - Cyber threats, misleading outputs and knowledge gaps were identified as the top three risks. The report also introduces a new framework to help firms understand how AI risk can emerge and spread across the financial services ecosystem. Read the full report: https://lnkd.in/gjupekSz

I've wondering when the embedded AI inside cyber tools really becomes effective? Right now they may help craft or validate a query, but in many ways it's still done like we did in 2022: alerts that need a second look by an analyst. We're able to get to that second look quicker with an agent but human critical thinking is needed. I've seen AI agents securely and effectively help manage investigations and the new kids on the block are getting better quickly. The EASY button may exist but I don't trust it....yet. And that's a dam expensive EASY button (see my last) post. <AI said I was repetitive on this post.>

This is a really timely report on how the world of financial services is adapting to AI and it really makes you think about "what is to come". Recommended reading for sure. Asif J. Matthew Edwards Mike Fenton MSc FIA Rajiv Gogna Kim Toker

"We run scans" is no longer a compliance answer. The EU Cyber Resilience Act — passed October 2024, enforcement from 2027 — requires documented, evidenced security testing throughout the development lifecycle. SEC cybersecurity disclosure rules, in force since late 2023, are pushing boards to demonstrate proactive security governance, not just react to incidents. Regulators want dated, reproducible, attributed evidence. A PDF export from a single-model scanner with no audit trail doesn't hold up. Neither does a manual review log that can't be reproduced. Mythos Preparation is built on ProvenanceOne's deterministic agentic platform. Every run is reproducible. Every finding is attributed to the specific AI agents — Claude, GPT-4o, Gemini, Llama — that raised it. That attribution creates a transparent chain of evidence: not just "a scanner flagged this," but which models agreed, which disagreed, and why the finding made it into the final report. The output is a Threat Briefing: a dated, structured artifact your compliance team can attach directly to audit submissions or board packs without reformatting. Security evidence generation stops being a pre-audit scramble and becomes a natural byproduct of your development workflow. See what auditable, multi-model AI security review looks like — and generate your first compliance-ready Threat Briefing today at https://lnkd.in/eukDF9QV #DevSecOps #AppSecurity #AICodeReview #ProvenanceOne

Cyberattacks keep evolving, and the tipping point from a "minor incident" to a major breach is often how quickly organizations can detect, investigate, and respond. The longer attackers stay undetected, the worse the damage gets. Prevention alone is no longer enough ☝️ Threat actors are now aggressively using AI to scale reconnaissance, phishing, malware creation, obfuscation, lateral movement, and data exfiltration — leveraging both mainstream LLMs and malicious AI tooling. At the same time, security teams face a growing resource mismatch. Not every alert or vulnerability can be analyzed manually with the same depth and speed. The market response? 🤔 Accelerated investment in automation. Since late 2024, the SOAR market has entered a new AI-driven renaissance, pushing the conversation beyond traditional rule-based automation toward what many now call the "Emerging AI SOC." 💡 For more insights like this, become a KuppingerCole Analysts Member: https://lnkd.in/es3YVQDm #AI #SOAR #LLMs

When attackers can weaponize AI to craft hyper-personalized lures or bypass traditional authentication through supply chain vulnerabilities, "standard" defense is a liability. It is time to pivot: • Zero Trust is non-negotiable: Move from static access to continuous, context-aware verification. If you aren't re-authenticating sensitive requests in real-time, you are vulnerable. • Beyond the "Human Firewall": Traditional security awareness training cannot keep pace with AI-generated deception. We must shift toward resilience—designing systems that assume human error and prevent single points of failure.  • Verify the Verbals: In an era of deepfakes and AI voice cloning, implement mandatory "trust codes" or out-of-band verification rituals for financial and high-stakes operational changes.  Security is no longer just an IT issue; it is a business survival strategy. Are your current defenses built for the reality of 2026 and beyond? #cysec #auguryIT