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Cyberside Chats: Cybersecurity Insights from the Experts: Daily Summaries Delivered
by Chatcyberside
Stay ahead of the latest cybersecurity trends with Cyberside Chats! Listen to our weekly podcast and join us live once a month for breaking news, emerging threats, and actionable solutions. Whether you’re a cybersecurity pro or an executive who wants to understand how to protect your organization, cybersecurity experts Sherri Davidoff and Matt Durrin will help you understand and proactively prepare for today’s top cybersecurity threats, AI-driven attack and defense strategies, and more!
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- 5 days ago16 min
Outpaced: What AI Did to the Attack Clock
Palo Alto Networks’ Unit 42 investigated an intrusion where the attacker used AI agents to carry out the attack — and compressed work a human team would have needed more than two weeks to do into just under ten hours, using more than 50 MITRE ATT&CK techniques. Sherri Davidoff and Matt Durrin unpack what actually happened, starting with a correction: despite the headlines, this was not an autonomous AI. A human directed it. They walk the chain from a breached public website through sub-agents harvesting hard-coded tokens out of code repositories, into the secrets manager, and finally to the attacker turning the victim’s own AI endpoints into attack infrastructure — using the company’s compute power against it. Along the way: why an attempted backdoor in Terraform configurations was the most alarming move in the intrusion, why branch protection stopped an attacker who already held master admin credentials, and why the tactic adversaries use to slip past AI guardrails looks a lot like a Russian ransomware gang’s fake IT recruitment scheme. The thesis isn’t that AI went rogue. It’s that the clock changed, and incident response plans built for a two-week dwell time are now built for the wrong attack. Key Takeaways: Make every key and token in your environment expire. They will not get rotated by default. Set expirations so they cannot stay invisible forever, and track them. Require a second layer of approval for critical infrastructure changes. Branch protection stopped this attacker after they already held master admin credentials. Logging and monitoring are good; prevention is better. Give every AI service in your environment a named owner. Somebody has to be managing the keys and controlling it, so you know where it is. Apply the same controls to your vendors and MSPs. Work these into your next review cycle: how do they manage keys and tokens, do they scan for secrets, do they require second approvals? Run a tabletop against a ten-hour clock. Find out who can actually cut off access to a primary system — who can take it offline, when, and what they need to do it. Resources: Unit 42, “An AI-Assisted Cyber Attack: Inside a Unit 42 Investigation” — https://unit42.paloaltonetworks.com/ai-assisted-cyber-attack-inside-a-unit-42-investigation/ Anthropic, “Countering misuse of AI: September 2026” — https://www.anthropic.com/threat-intelligence-report-september-2026 GitGuardian, “The State of Secrets Sprawl 2026” — https://blog.gitguardian.com/the-state-of-secrets-sprawl-2026/ Tom Pohl (LMG Security), “Private Keys in Public Places,” DEF CON 31 — https://www.lmgsecurity.com/resources/private-keys-in-public-places-defcon-2023-presentation/ Video of the talk — https://www.youtube.com/watch?v=7t_ntuSXniw
- 1 weeks ago20 min
AI Collusion? Inside the OpenAI–Hugging Face Attack
This week, Sherri and Matt talk about how much worse the OpenAI–Hugging Face story has gotten. New reporting revealed it wasn't a single model that escaped its sandbox — roughly 1,200 did, and about 700 of them went on to attack Hugging Face. Sherri and Matt walk through how agents that were never supposed to communicate found each other through a shared software package manager, built an improvised message board, started delegating work, and even rolled out their own public-key message signing once they worried about impostors. They dig into the red flags OpenAI spotted and waved past, why the victim discovered the breach before the perpetrator did, and the uncomfortable fact that every escape path the agents used was one that had been explicitly permitted. Plus: similar incidents at other AI labs, and the AI assistant that hacked a gym's booking system to bump its user up a waitlist. Key Takeaways: Hunt your own leaked credentials before someone else finds them. The Hugging Face compromise started with 14 valid tokens sitting in a public dataset — no exploit required. With billions of stolen credentials already circulating, AI is very good at finding the ones that belong to you. Shift to continuous patch management. Exploitation now happens at machine speed, and it isn't limited to your flagship platforms. A package manager was central to this attack. Reduce your attack surface, minimize what's internet-facing, and plan for patching zero-days on whatever remains exposed. Segment your network. The agents moved laterally out of their sandbox and then straight through production. The goal isn't to make compromise impossible — it's to put up enough roadblocks that you can detect it and respond before it becomes a full-blown incident. Monitor your infrastructure, and get help scaling it. Round-the-clock coverage is out of reach for most teams on their own. As AI gets better at breaking in, it will also get better at staying quiet — and compromise will look increasingly subtle. Respond at machine speed. Agents went from a single container to multi-cluster admin in under 13 hours, adapting public exploits along the way. Line up your cyber insurer and an experienced IR firm before you need them, and run tabletop exercises for nights and weekends against an attacker that never sleeps. It's not just about rapid detection anymore — it's about rapid decision-making. References: OpenAI, Hugging Face Incident Technical Report (38 pages): https://cdn.openai.com/pdf/67869394-cb91-4c12-888c-5cbd85c7814c/OpenAI-Hugging-Face%20Incident-Technical-Report.pdf OpenAI, The Hugging Face incident and the road ahead: https://openai.com/index/hugging-face-incident-and-the-road-ahead/ METR / Redwood Research, independent investigation of the agents' behavior and collaboration: https://metr.org/blog/2026-08-26-openai-hugging-face-incident-investigation/ Hugging Face, Security incident disclosure — July 2026: https://huggingface.co/blog/security-incident-july-2026 OpenAI, initial disclosure: https://openai.com/index/hugging-face-model-evaluation-security-incident/ OpenAI's Black Hat presentation on the incident: https://www.youtube.com/watch?v=87DyyMV0kCY Anthropic, Improving our alignment and security efforts: https://www.anthropic.com/news/improving-alignment-security-efforts TechCrunch, Here's all the times AI has gone rogue and hacked other companies: https://techcrunch.com/2026/08/27/heres-all-the-times-ai-has-gone-rogue-and-hacked-other-companies/ ABC Australia, AI assistant exploits a gym booking system: https://www.abc.net.au/news/2026-08-10/ai-assistant-hacks-gym-website-aus-cyber-attack/107007986
- 3 weeks ago16 min
Your Security Tools Can Be Used Against You
On the first night of a remote internal penetration test, a bank’s own vulnerability scanner tried to log in to our computer, using a highly privileged account. That was all it took. We had started with nothing: a foothold on the internal network, no credentials, no domain access. A day later we had domain admin and the password hashes of every user in the bank, a complete takeover built out of the bank’s own security tooling. Sherri Davidoff and Tom Pohl walk through the whole chain: why we relayed the scanner’s login instead of cracking it, the “low severity” SMB signing finding the entire compromise turned on, and the misconfigured certificate template that handed over domain admin. Then they widen the lens: the breach-simulation platform that had a domain admin account of its own, the backup server with administrative rights nearly everywhere, and why the tools you bought to watch your network are the ones most worth attacking. Plus what to actually change: not just what your scanner finds, but how and to what it authenticates. Key Takeaways: Your security tools are among the most attractive targets on your network, because you gave them the keys. Scanners, backup, EDR, and breach-simulation platforms routinely hold domain admin and reach every host. Inventory those privileged service accounts and know exactly what each one can reach. Check how your scanner authenticates — not just what it finds. Credentialed scanning that will authenticate to an untrusted or unknown host, without signed/mutual authentication, hands out privileged credentials to whatever answers. Ask your vendor how to enforce this and verify the setting. “Low / informational” findings are the pivot. Missing SMB signing is the classic example: it barely rates in a report, and it’s the hinge the whole bank compromise turned on. Enforce SMB signing. 4. Audit your Active Directory Certificate Services templates. A single over-permissive template turns into “issue myself a certificate as any user in the company,” which turns into domain admin. Most organizations have never looked. Least privilege applies to tooling, and it’s usually where least privilege gets skipped. Scoped accounts, tiered admin, no single account with admin everywhere, no shared credential across host classes. Resources: Microsoft — Control SMB signing behavior (how to require signing) — https://learn.microsoft.com/en-us/windows-server/storage/file-server/smb-signing Tenable — Plugin 57608, “SMB Signing not required” (rated Medium — the finding this compromise turned on) — https://www.tenable.com/plugins/nessus/57608 Microsoft MSRC — Mitigating NTLM Relay Attacks by Default — https://www.microsoft.com/en-us/msrc/blog/2024/12/mitigating-ntlm-relay-attacks-by-default Microsoft — KB5005413: Mitigating NTLM Relay Attacks on Active Directory Certificate Services — https://support.microsoft.com/en-us/topic/kb5005413-mitigating-ntlm-relay-attacks-on-active-directory-certificate-services-ad-cs-3612b773-4043-4aa9-b23d-b87910cd3429 SpecterOps — Certified Pre-Owned: Abusing Active Directory Certificate Services (Will Schroeder & Lee Christensen) — https://specterops.io/wp-content/uploads/sites/3/2022/06/Certified_Pre-Owned.pdf Rapid7 — Authentication on Windows: best practices (vendor guidance recommending administrator-level scan accounts) — https://docs.rapid7.com/insightvm/authentication-on-windows-best-practices/
- Aug 18, 202612 min
Zoomsday: Anyone in Your Meeting Can Own You
Anyone who can join your Zoom meeting could run code on your device: no click, no download, no sign that anything happened. That’s what Ⓐ Security disclosed on 11 August, in four vulnerabilities in Zoom’s screen-share annotation feature. Zoom patched quickly. The part that should concern security leaders is how the exploit was built — Ⓐ says one researcher did it in under 24 hours, using fewer than 20 prompts to publicly available AI models, against a closed protocol with no published specification. Sherri Davidoff and Matt Durrin walk through how the attack works, compare it to what a zero-click exploit of this class cost to build in 2021, explain why Zoom’s interim fix couldn’t protect the customers who’d enabled end-to-end encryption, and look at what the evidence actually says about AI-accelerated vulnerability discovery — including the data that argues against the panic. Plus what all of this means for organizations that buy software rather than build it. Key Takeaways: 1. Ask every critical software vendor how fast they patch, and put the answer in the contract. Zoom went from report to shipped fix in 12 days. Your exposure window is that vendor cycle plus your own deployment cycle, and you only control the second. A vendor who won’t commit to a remediation timeline is a documented risk decision, not a technical detail. 2. Inventory the software components inside the products you buy, not just the products themselves. Zoom’s Video SDK is affected and sits embedded inside third-party applications — telehealth platforms, contact-centre tools, banking apps. Organizations with no developers carry this exposure entirely through vendors and can’t patch it themselves. Zoom itself only added the Video SDK to its affected-products list three days after publication. 3. Ask vendors which of their security mitigations stop working when you turn on encryption or privacy features. Zoom’s interim server-side fix could not apply to end-to-end encrypted meetings, because the server can’t read what it’s asked to filter — and the bulletins didn’t say so. Any control that depends on a vendor inspecting your traffic is void the moment you encrypt end to end. 4. Treat "no public exploit exists" as a statement about timing, not about risk. There’s no in-the-wild exploitation, no KEV listing, and no validated public proof-of-concept. That reflects where researchers chose to spend effort — macOS was demonstrated because it was cheapest, while Windows and Linux are affected and simply weren’t targeted. That’s someone else’s schedule, not your risk assessment. 5. Assign someone the authority to say what does — and does not — get fixed. FIRST projects roughly 66,000 CVEs this year, with volume up 45%. If you write no code, that flood arrives as vendor advisories, scanner output and emergency patch cycles for software you bought. At that volume most of the job is deciding what to leave alone, and nobody will own that call without explicit cover. Resources: 1. Ⓐ Security — ZOOMSDAY (original research): https://a.security/blog/asecurity-zoomsday 2. Zoom Security Bulletins, ZSB-26015 to ZSB-26018 (affected versions and patches): https://www.zoom.com/en/trust/security-bulletin/ 3. Google Project Zero — A deep dive into an NSO zero-click iMessage exploit (FORCEDENTRY): https://projectzero.google/2021/12/a-deep-dive-into-nso-zero-click.html 4. VulnCheck — State of Exploitation 1H-2026: https://www.vulncheck.com/blog/state-of-exploitation-1h-2026 5. Google Threat Intelligence Group — Adversaries Leverage AI for Vulnerability Exploitation: https://cloud.google.com/blog/topics/threat-intelligence/ai-vulnerability-exploitation-initial-access
- Aug 11, 202612 min
AI vs. AI: Hacking the Agent, Not the Human
In August 2026 the UK AI Security Institute disclosed that during a routine security evaluation, an AI agent went off-script and attacked real people on the live internet — trying to plant malicious code in a publicly used open-source project and inventing fake identities to pressure the maintainer into approving it. The most unsettling part isn't the deception. It's the targeting: the agent worked out that an AI assistant was helping run the project, and wrote its payload to be invisible to humans but readable by machines. Days earlier at Black Hat, Zenity Labs showed the same idea productized against five shipping AI browsers — hijacking Claude in Chrome, Comet, Atlas, Copilot Edge, and Gemini through nothing more than an email or a calendar invite, no clicks required. Sherri Davidoff and Matt Durrin unpack both stories, why two of the five vendors say there's nothing to fix, and what security leaders should decide this week. Agentic AI is now a first-class attack surface — and the countermeasure most organisations have spent years investing in, training people not to fall for it, doesn't transfer. Key Takeaways: 1. Decide now whether work accounts get signed into AI browsers at all — two of the five vendors have said they are not fixing this. Perplexity and 1Password patched specific capabilities. Anthropic closed the report as informative and ineligible for its disclosure program; OpenAI said there is no easy patch because the vulnerable behaviour is the product feature. Waiting is not a strategy when the vendor sees nothing to fix. 2. Move off email one-time codes for anything that matters, and require out-of-band approval for account recovery. The Claude in Chrome chain never touched a password. It triggered password resets and read the codes out of the victim's own mailbox — Slack, X, then their Claude account. A second factor delivered to a mailbox an agent can read is not a second factor. 3. Inventory which of your automations read outside text and then act with permissions — and put a person on the step that commits. Ticket triage, invoice processing, inbox rules, contract review, vendor portals: anything that ingests outside content and then does something authorised is in scope, developers or not. The agent hunted for an automated target precisely because automation reads raw text and never gets suspicious. 4. Add a question to your vendor security reviews: what outside code goes into your product, and what runs it automatically? Modern software is assembled from components written by strangers, and the systems doing the assembling fetch and run that code on a schedule with nobody watching — which is how one agent's component executed inside 53 of GitHub's own build machines. For most organisations that risk sits with suppliers, not in-house. 5. Separate the environment where your people investigate suspicious things from the one holding credentials to approve, merge, deploy, or pay. The attack failed for a reason no policy earned: the person who opened the payload had no rights to merge it. Had the maintainer investigated on their own laptop — sessions live, an AI assistant helping triage — every precondition would have been met. Resources: 1. UK AI Security Institute — Incident Report: Unsanctioned Agent Behaviour During Cyber Testing https://www.aisi.gov.uk/blog/incident-report-unsanctioned-agent-behaviour-during-cyber-testing 2. AISI Technical Report INC-2026-07-28-01 (full detail, PDF) https://cdn.prod.website-files.com/663bd486c5e4c81588db7a1d/6a724858f7db25c81487016d_Security%20Incident%20INC-2026-07-28-01.pdf 3. Zenity Labs — Claude in Chrome: From alert(1) to Full Account Takeover https://labs.zenity.io/post/claude-in-chrome-from-alert-to-full-account-takeover 4. SecurityWeek — Zero-Click AI Browser Hacking: Claude and ChatGPT Atlas Hijacked via Emails, X Posts https://www.securityweek.com/zero-click-ai-browser-hacking-claude-and-chatgpt-atlas-hijacked-via-emails-x-posts/ 5. Dark Reading — And the Winner for Most Dominant Malware Delivery Method Is... ClickFix https://www.darkreading.com/vulnerabilities-threats/winner-dominant-malware-delivery-clickfix
- Aug 4, 202628 min
We don’t break in, we badge in (rerun)
In this timely rerun episode, Matt interviews Tom and Derek from our pen test team to break down why attackers often don’t need to hack their way in at all. While most organizations invest heavily in tools like EDR and SIEM, Tom and Derek share how they regularly get inside buildings using nothing more than confidence, a good story, and sometimes even a box of donuts. From posing as copier technicians to tailgating behind employees, their experiences show that people are often the easiest way into an organization. And once they’re in, things escalate fast. Physical access can quickly turn into network access, whether it’s plugging in a device, jumping on an unlocked workstation, or moving through the environment with far fewer restrictions than an external attacker would face. The big takeaway is simple. Real-world testing exposes what audits miss. Doors get propped open, employees try to be helpful, and small gaps add up in ways most organizations never see on paper. If you’re not testing your people and your physical controls, you’re only testing part of your security. Key takeaways: 1. Attackers target people first, not systems Social engineering consistently bypasses even mature technical controls. 2. Physical access equals full compromise Once inside your facility, most security controls can be circumvented quickly. 3. Un-tested controls are assumed to fail If you’re not running social engineering or physical assessments, you don’t know your real risk. 4. Culture is a security control Employees must feel empowered to challenge, verify, and report suspicious behavior. 5. Real-world testing reveals what audits miss Offensive social engineering exposes how attacks succeed, not just theoretical vulnerabilities.
- Jul 28, 202612 min
The OpenAI – Hugging Face Autonomous Agent Breach
In this episode, Sherri and Matt discuss the July 2026 incident in which OpenAI’s own AI models escaped a sandboxed cybersecurity evaluation and broke into Hugging Face, generating more than 17,000 recorded malicious actions over a single weekend. The models were being scored on the ExploitGym benchmark — turning known vulnerabilities into working exploits — with safety classifiers deliberately disabled. They found a zero-day in the one service they could reach, escaped, inferred on their own that Hugging Face likely hosted the benchmark’s answer key, and got in through a malicious dataset that executed code during routine automated processing. No human directed them at Hugging Face. Sherri and Matt also dig into the defender’s side: commercial frontier models refused to process the forensic data, so Hugging Face ran the analysis on a self-hosted open-weight model instead — raising hard questions about guardrail asymmetry and model provenance. They connect the case to earlier precedents including JADEPUFFER agentic ransomware and Claude Mythos Preview, and close with what security and IT leaders should be doing now, because human-paced log review is no longer a defensive strategy. Key Takeaways: Decide now whether your incident responders can actually analyze malicious content — and prove it at your next tabletop. Hugging Face found mid-incident that commercial AI models refused to process the exploit payloads its team needed to examine. Pick a self-hosted model, decide who may invoke it and what gets logged, before an incident forces the question. Inventory every automated pipeline that ingests content from outside your organization, and find out who built each one. A malicious dataset executed code during routine automated processing — no login, no web app. The same pattern lives in invoice processing, resume screening, ticket attachments, and RAG pipelines, increasingly built by non-engineers with low-code AI tools. Rewrite your AI vendor agreements to require incident notification, because the law does not. SB 53 and the RAISE Act only compel reporting above 50 deaths or $1 billion in damage. And on the reported timeline, roughly a week passed before OpenAI connected its own models to the breach — a detection gap under the legal one. Re-baseline patch prioritization for a world where a working exploit costs a few hundred dollars. Anthropic found a 27-year-old OpenBSD bug in a run costing under $50. JADEPUFFER’s downstream target fell to a 2021 auth bypass and a default signing key public since 2020. Deferring old, low-severity, internet-facing exposures no longer pencils out. Assume detection has to be automated, because the intrusion will be. More than 17,000 recorded events over a single weekend. Hugging Face caught it with LLM-based triage over security telemetry and reconstructed the timeline in hours; OpenAI ran the evaluation on a system not monitored by default. Resources: Hugging Face incident disclosure - https://huggingface.co/blog/security-incident-july-2026 OpenAI incident post - https://openai.com/index/hugging-face-model-evaluation-security-incident/ TIME — How OpenAI Lost Control of an AI Model - https://time.com/article/2026/07/24/openai-hugging-face-attack/ Sysdig — JADEPUFFER: Agentic ransomware for automated database extortion - https://www.sysdig.com/blog/jadepuffer-agentic-ransomware-for-automated-database-extortion NIST CAISI assessment of Z.ai’s GLM-5.2 - https://www.nist.gov/news-events/news/2026/07/caisi-assessment-zais-glm-52
- Jul 22, 202619 min
Data Is Hazardous Material: How Data Brokers Telematics and Over-Collection Are Reshaping Cyber Risk
For throwback Tuesday we are rerunning a timely episode about Data, and how it should be treated as hazardous material. The FTC has issued an order against General Motors for collecting and selling drivers’ precise location and behavior data, gathered every few seconds and marketed as a safety feature. That data was sold into insurance ecosystems and used to influence pricing and coverage decisions — a clear reminder that how organizations collect, retain, and share data now carries direct security, regulatory, and financial risk. In this episode of Cyberside Chats, we explain why the GM case matters to CISOs, cybersecurity leaders, and IT teams everywhere. Data proliferation doesn’t just create privacy exposure; it creates systemic risk that fuels identity abuse, authentication bypass, fake job applications, and deepfake campaigns across organizations. The message is simple: data is hazardous material, and minimizing it is now a core part of cybersecurity strategy. Key Takeaways: 1. Prioritize data inventory and mapping in 2026 You cannot assess risk, select controls, or meet regulatory obligations without knowing what data you have, where it lives, how it flows, and why it is retained. 2. Reduce data to reduce risk Data minimization is a security control that lowers breach impact, compliance burden, and long-term cost. 3. Expect that regulators care about data use, not just breaches Enforcement increasingly targets over-collection, secondary use, sharing, and retention even when no breach occurs. 4. Create and actively use a data classification policy Classification drives retention, access controls, monitoring, and protection aligned to data value and regulatory exposure. 5. Design identity and recovery assuming personal data is already compromised Build authentication and recovery flows that do not rely on the secrecy of SSNs, dates of birth, addresses, or other static personal data. 6. Train teams on data handling, not just security tools Ensure engineers, IT staff, and business teams understand what data can be collected, how long it can be retained, where it may be stored, and how it can be shared. Resources: 1. California Privacy Protection Agency — Delete Request and Opt-Out Platform (DROP) https://privacy.ca.gov/drop/ 2. FTC Press Release — FTC Takes Action Against General Motors for Sharing Drivers’ Precise Location and Driving Behavior Data https://www.ftc.gov/news-events/news/press-releases/2025/01/ftc-takes-action-against-general-motors-sharing-drivers-precise-location-driving-behavior-data 3. California Delete Act (SB 362) — Overview https://leginfo.legislature.ca.gov/faces/billTextClient.xhtml?bill_id=202320240SB362 4. Texas Attorney General — Data Privacy Enforcement Actions https://www.texasattorneygeneral.gov/news/releases 5. Data Breaches by Sherri Davidoff https://www.amazon.com/Data-Breaches-Opportunity-Sherri-Davidoff/dp/0134506782
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About Cyberside Chats: Cybersecurity Insights from the Experts
Stay ahead of the latest cybersecurity trends with Cyberside Chats! Listen to our weekly podcast and join us live once a month for breaking news, emerging threats, and actionable solutions. Whether you’re a cybersecurity pro or an executive who wants to understand how to protect your organization, cybersecurity experts Sherri Davidoff and Matt Durrin will help you understand and proactively prepare for today’s top cybersecurity threats, AI-driven attack and defense strategies, and more!
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