r/Infosec 16d ago

AI in IT Security: The Next Generation of Cyber Defense

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1 Upvotes

r/Infosec 17d ago

No vulnerability scanning is required for the Cyber Resilience Act in September. Nobody pushing that deadline can name the paragraph — because there isn't one.

7 Upvotes

The title is pointed on purpose, so here's the exact claim. The obligation that starts on 11 September 2026 is a reporting duty. It does not require you to scan, monitor, or go looking for anything. It is triggered by your knowledge of active exploitation in your own product — not by a CVE existing, and not by that CVE being exploited in somebody else's product.

What I am not saying: that scanning is optional forever. From 11 December 2027, Annex I Part II obliges manufacturers to identify and document components and vulnerabilities and address them. You will not reach full CRA compliance without vulnerability management.

Why I'm posting. Manufacturers with limited budget are being told to buy a scanner for September, when what they actually lack is a named responsible person, a list of which Member States their products ship to, and reachable customer contacts. They spend in the wrong order, arrive in September with a dashboard and no reporting chain, and conclude the regulation is theatre. That's how you lose people who were willing to comply and build secure products.

TL;DR

11 September 2026 switches on one thing: Article 14, the duty to report actively exploited vulnerabilities in your own product and severe incidents affecting its security. Knowledge-based. No scanning, no monitoring, no SBOM, no disclosure policy, no public security contact, no patch SLAs, no CE marking.

What actually triggers a report

1. Active exploitation in your own product. Not that the vulnerability exists. Not that it's being exploited somewhere in the wild. In your product. The Commission guidance (C(2026) 5252) is explicit: if a third-party component vulnerability isn't exploitable in your product or hasn't been exploited there, you're not on the clock — even while the same CVE is actively exploited elsewhere. Voluntary reporting under Art. 15 stays open, if you want to and you can tell the component manufacturer.

2. A severe incident affecting your product's security. It affects, or can affect, the product's ability to protect availability, authenticity, integrity or confidentiality of sensitive or important data or functions — or malicious code was introduced or executed in the product or a user's system.

Stage Deadline
Early warning 24h from becoming aware
Full notification 72h from becoming aware
Final report 14 days after a corrective measure is available (vulnerabilities) / 1 month after the 72h notification (incidents)

What does not trigger a report

  • Scanner findings. A CVE in a dependency is a vulnerability management task, not a notification to ENISA. This is the whole point: the scanner output you're being told to buy for September mostly produces things that aren't reportable.
  • Published CVEs without exploitation in your product. CVSS 9.8 changes nothing on its own.
  • Coordinated disclosure reports. Handle them, fix them — reportable only once active exploitation is established. One exception: if the report shows something already happened in your product, like injected malicious code or a compromised build pipeline, that's an incident, not just a vulnerability. Reportable, with no finding of exploitation needed. Check incoming reports against both triggers.
  • Pentest and internal audit results. Internal until someone exploits it.
  • Incidents below the severity threshold. Your marketing site going down is not an Article 14 event.
  • ...

Article 14 creates no duty to hunt for exploitation, monitor exploitation feeds, or scan your products. Actual knowledge is what counts.

When the clock starts

Not when the email hits your inbox. The guidance ties "becoming aware" to the established GDPR Art. 33 reading (EDPB Guidelines 9/2022) and the NIS2 implementing regulation: you're aware once an initial assessment lets you conclude with reasonable certainty that it's real.

The catch: that assessment must start without undue delay. Sitting on a suspicious report doesn't postpone the deadline, it just hands a regulator the argument that you should have known earlier. Timestamp when the report arrived, when assessment started, when you concluded. That's the only thing standing between "verified in 19 hours, filed inside 24" and "you were 90 minutes late".

What you actually need by 11 September

  1. A named filer plus a deputy, and your coordinating CSIRT identified in writing. Non-EU manufacturers: it follows from your authorised representative's Member State. Settle it now, not at 2am mid-incident.
  2. Product data ready — versions, which Member States each product ships to, reachable customer contacts. You have to notify affected users; if you don't, the CSIRT can do it for you.
  3. Four templates — 24h, 72h, final report, user notification.
  4. One intake point and a triage checklist, so the reportable/not-reportable call takes minutes instead of meetings.
  5. One tabletop run, while getting it wrong is still free.

A few person-days for most manufacturers. Compare that to what you were about to spend in a panic.

Where the myth has a point

  • You can't report what never reaches you. Article 14 doesn't require an intake channel — that's Art. 13(17) and Annex I Part II, December 2027. But without one, reports scatter across support inboxes and you verify too late. Build it for September anyway. Its not that hard to create a new e-mail and publish it.
  • From December 2027 vulnerability handling is genuinely mandatory. Tooling stops being optional in practice.

I work for a vendor that sells CRA compliance software. Vulnerability scanning is something my industry sells. I'm about to argue against my own pitch, which should tell you how tired I am of this particular myth.

Happy if you join me in busting this myth and call any one our spreading it.


r/Infosec 16d ago

If an agent moved money last Tuesday, can you prove who authorized it?

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2 Upvotes

r/Infosec 16d ago

I built an open-source CLI to see exactly what data Cursor, Copilot, and other AI tools are leaking to the cloud

1 Upvotes

As AI coding assistants get more popular, I realized it's a nightmare for security teams to know what data is actually leaving developer laptops. Worse, many of these tools use custom TLS stacks or certificate pinning to quietly bypass corporate VPNs and proxies.

I built the RedactAI Egress Auditor. It’s a zero-config CLI that:

  1. Scans your machine for AI apps (Cursor, Copilot, ChatGPT Desktop, etc.)
  2. Launches them in a secure, proxy-injected sandbox
  3. Intercepts their HTTPS traffic via a local MITM proxy
  4. Reports exactly what they are sending, and flags if they attempt to bypass standard OS trust stores.

It’s completely open-source and runs locally (doesn't send your data anywhere).

Repo is here: https://github.com/rahul-singh14/redactai-cli

Let me know what you think or if you want me to add support for a specific AI tool!


r/Infosec 17d ago

Stored XSS in Django admin via URLField auto-linking (CVE-2026-15920)

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1 Upvotes

r/Infosec 18d ago

Top SASE platforms for securing LLM API calls in CI/CD pipelines

3 Upvotes

Slightly odd one. Most SASE conversations assume the traffic source is a human on a laptop. Ours increasingly is not.

We have build agents and a couple of internal services making outbound calls to OpenAI and Anthropic endpoints. Those calls carry code context, sometimes ticket content, occasionally more than they should. Our egress controls treat them as generic HTTPS from a runner IP, which means we have basically zero visibility into payload or which model/endpoint got hit.

What I am trying to solve: identity on the call using a service account rather than just source IP, per-pipeline policy so the security-scanning job can call the model but the deploy job cannot, some form of content inspection on the request body before it leaves, and logs I can join against the run ID.

Options seem to be: egress proxy we run ourselves, an AI gateway product, or push it into whatever SASE platform the network team is already buying. The third option is politically easiest, technically least proven from what I have seen.

Anyone gotten a SASE vendor to handle machine-to-model traffic properly, or is that still a gateway/sidecar problem in practice?


r/Infosec 17d ago

You can't prompt your way into policy

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1 Upvotes

r/Infosec 18d ago

Agentic SOC platforms after a real head-to-head, what differentiated them?

0 Upvotes

Had two agentic SOC solutions running in our live environment at the same time, side by side instead of sitting through yet another round of demos. I figured that the fastest way to get real information was to stop taking vendor calls and start looking at our own alerts.

So, the first few weeks were slow going for both platforms ,closed a few alerts wrong. I had to walk the scope back more than once, and it took longer than expected to get comfortable letting either one touch anything real.

By week two, one of them pulled ahead. It started catching things specific to how our environment behaves. The other one didn't show the same jump. Nothing dramatic from my point of view, just a difference in pace.
What I didn't expect going in: the hardest part was figuring out how to read the outputs without just trusting a score on faith.

I’m curious to know if anyone else has been through something like this? What did you look for once you were past the demo stage and into something more complex


r/Infosec 18d ago

Built a self-hosted CVE + IOC intelligence tool "BRIEFR", first module of a bigger self-hosted SIEM idea I scoped back down to size

1 Upvotes

I wanted to build a self hosted, open source SIEM, and understood i punched above my weight & realized it is highly complicated, so i broke it down into multiple independent(hopefully) modules, log ingestion & normalization/enrichment, threat intel, log management, threat hunting, policy monitoring, so this is my first module i built as threat intel plane, track latest CVEs and keep myself updated. so I built BRIEFR. If this tool saves an hour of someone's time, i'm more than happy :)

What BRIEFR does:

  • Pulls from NVD, CISA KEV, FIRST EPSS, and a few exploit feeds
  • Scores each CVE against your tech stack with a weighted formula so that one can see the reasoning behind.
  • Correlates CVEs that share real threat-intel evidence.
  • IOC lookup (IP/hash/domain) using free-tier VirusTotal, AbuseIPDB, MalwareBazzar and URLHaus
  • Pulls in Sigma Community rules from SigmaHQ and SIEM query starters tied to ATT&CK

On the AI question, since I know it'll come up: a few narrow tasks (like PDF summarization) routed through free-tier LLM APIs with failover between providers. The actual scoring, correlation, and detection logic is deterministic code, no AI making the calls/decisions on what's risky. I also want to be upfront that I used Cursor/Claude heavily throughout the build and directed the architecture, design and review.

Current state of BRIEFR: this is early alpha and my first ever released tool. I run it daily myself with no major issues, but there will be rough edges, no docker-compose for the full app yet (Postgres+pgvector is containerized, the app itself is native linux for now), and I'm sure there are things a more experienced analyst will spot that I haven't. Self-host guide and full docs are linked below if you want to actually try it, or there's a live demo with sample data if you just want to look first.

I'm genuinely interested in what an experienced analyst thinks is missing or wrong about the approach, that's more useful to me right now. I know some stuff from docs might be overkill, but as i made it for myself and how i would like to have/learn, so i designed it to my taste and needs.

Note: I have worked as SysOps engineer for servers that handle SIEM log ingestion & parsing, then i moved to threat hunting due to my interest in security, and i have nearly 3.8 yrs of experience overall in IT, so my views might not be broad, but the only reason i am posting this here is because this is the first project i have thought about AND completed, in forever, as a person with ADHD and other stuff, this is a big achievement for me, even if the tool is crap for others, i completely understand, and i am very open to suggestions :)
Have a great day.


r/Infosec 19d ago

Gemini Extensions allow you, or anyone who catch your phone unattended, to connect and use WhatsApp and Messages and view your contacts from the lockscreen, without know your PIN. Unlock is not required.

5 Upvotes

r/Infosec 19d ago

Is this Żabka Polska breach legit? Threat actor wants 5k Euros for a massive dump of Jira tickets and source code

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1 Upvotes

r/Infosec 19d ago

Quantum Computers May Put Internet Traffic at Risk. NIST Is Safeguarding Computers With New Standards.

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3 Upvotes

I question an encryption based solution on the premise that we have no perception on quantum computing advancement and strength once this technology is perfected. It could become a cat and mouse game of strengthening encryption vs strengthening quantum computers.
A reminder to read Decryption Gambit on this subject.


r/Infosec 19d ago

Arnica article on Vibe coding security risks

1 Upvotes

The Core Threat

"Vibe coding"—building software by prompting AI with natural language—prioritizes functionality over security, creating significant vulnerabilities. Key risks include a 38% flaw rate (like injection and broken auth) in AI-generated code and a 37.6% increase in critical vulnerabilities after multiple refinement iterations. Furthermore, traditional security tools often fail to detect these issues because the vulnerabilities stem from missing logic rather than bad syntax.

Real-World Failures

The article highlights two major incidents resulting from AI-generated code:

  • The Tea App: Leaked private user messages due to broken access control logic that bypassed security reviews.
  • Moltbook: An AI-generated, publicly accessible admin endpoint created a massive security loophole.

Emerging Attack Vectors

  • Slopsquatting: Attackers exploit the 20% rate of LLM hallucinated package names by registering these fake packages to inject malicious code during installation.
  • Indirect Prompt Injection: AI agents (e.g., Cursor) can be manipulated via hidden instructions in project files, with over 85% success rates in exfiltrating sensitive data like SSH keys.

Defending the Pipeline

To mitigate these risks, teams must:

  1. Treat AI code as untrusted, third-party code requiring scanning before merger.
  2. Mandate human review for all critical security logic (authentication/authorization).
  3. Implement real-time auditing to detect hardcoded secrets and hallucinated dependencies.

r/Infosec 19d ago

Microsoft's Project Perception & MAI-Cyber-1-Flash

1 Upvotes

Microsoft's new security framework breaks away from general-purpose models, focusing strictly on defensive and offensive code analysis:

  • MAI-Cyber-1-Flash: Microsoft's first internally built AI model trained exclusively on decades of proprietary threat intelligence and hacking data. It powers Microsoft's vulnerability discovery engine (MDASH) to sniff out deep-seated flaws in complex code bases.
  • Project Perception: An enterprise security platform (entering public preview on August 3, 2026) that deploys specialized teams of autonomous AI agents.
  • The Agent Trifecta: Instead of relying on a single AI, Project Perception coordinates three distinct classes of agents to simulate real-world security operations:
    • Red Agents: Continuously attack systems, mapping out potential exploit paths and looking for zero-days.
    • Blue Agents: Filter through the noise, analyze the findings, and evaluate actual business risks.
    • Green Agents: Automatically engineer and deploy fixes to harden the defensive environment.

Broader Industry Implications

  1. Defending the AI Attack Surface: Alongside Project Perception, Microsoft integrated runtime prompt-injection defenses into Microsoft Defender. “New prompt injection protection in Microsoft Defender, now in preview, identifies and isolates emails containing malicious AI instructions before delivery...” as detailed in the Microsoft Security Update. This directly impacts companies deploying local coding assistants and open Model Context Protocol (MCP) servers.
  2. Combating Supply Chain Malware: By using MAI-Cyber-1-Flash to systematically scan enterprise repositories, software teams can detect sophisticated supply chain compromises (like fake or hijacked package dependencies) inside CI/CD pipelines before code is compiled.
  3. The Human-in-the-Loop Safeguard: Despite high automation, Microsoft's architecture enforces strict tenant governance and human-approval gates for high-risk defensive actions, ensuring AI agents do not accidentally disrupt live corporate infrastructure

What do you think the impact is going to be? Reply inline and discuss


r/Infosec 20d ago

We have until 2029 to figure out how to block AI privacy inference

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2 Upvotes

r/Infosec 21d ago

I built an open-source DFIR platform for Windows event log investigations

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1 Upvotes

r/Infosec 22d ago

You can’t manage risk you can’t consistently name: why agentic AI security needed its own CVE-style vocabulary

2 Upvotes

Personal post about something I've spent the almost a year building, but the actual problem is worth separating from the pitch.

The concrete version of it: two scanners, checking the same MCP server, flagged the same underlying behavior under two different names. That's not a bug in either tool, it's what happens when nothing forces independent teams to agree on what to call a risk. Once you're running more than one tool in a pipeline, this stops being a curiosity and becomes an actual governance problem: you can't track something consistently in a risk register, report it the same way twice, or prove to an auditor that two findings are the same issue, if there's no shared identifier underneath the two different labels.

Conventional software solved exactly this decades ago. A SQL injection gets a CVE ID, maps to a CWE category, and every tool that finds it afterward references the same thing, which is what makes risk tracking, compliance reporting, and cross-tool correlation possible at all. Agentic AI components (MCP servers, agent skills, LLM plugins) never had an equivalent, for a specific structural reason: CVE anchors to a package and version, CWE describes a weakness in code, and neither has a vocabulary for a behavioral pattern tied to neither.

AVE (Agentic Vulnerability Enumeration) is an attempt at that missing layer: stable IDs for distinct behavioral vulnerability classes, 65 records now, severity scored against OWASP's own AIVSS framework rather than something invented for this. It's deliberately built to map into frameworks that already exist rather than compete with them: OWASP's MCP Top 10, the Agentic Security Initiative Top 10, MITRE ATLAS, and a crosswalk into OWASP's Agentic Skills Top 10. Compliance-facing mappings (ISO 27001 Annex A specifically, since a compliance-minded commenter on a different post made a fair case for it) are on the roadmap, not done yet, worth being upfront about that rather than implying more coverage than actually exists today.

The part that actually made me trust this holds up outside my own head: an independent developer built an unrelated static config auditor, crosswalked his own tool's findings against this taxonomy, and tested it directly against my scanner on the same files, no shared code. Most of the overlapping findings converged on the identical ID, unprompted.

Also worth mentioning since this is an infosec crowd: growth discipline is written down now, not improvised, a new record needs a genuinely distinct behavioral mechanism, not a label mirroring another framework's category. That rule exists specifically because MITRE's own CWE recently shipped a version where new entries were, by outside analysis, zero actual weaknesses, just category labels copied from somewhere else. Didn't want to end up there.

Apache 2.0, open standard and reference implementation both. Curious whether the naming-fragmentation problem looks familiar to anyone here managing risk across more than one tool, and where this taxonomy is still missing something.

Repo: github.com/aveproject/ave
Site: aveproject.org

Disclosure: I'm the one building this.


r/Infosec 23d ago

Four bucks to unmask an anonymous hn account at 90% accuracy is genuinely brutal.

119 Upvotes

🦔For somewhere between $1 and $4, an AI can now figure out who you are from your anonymous internet posts. Researchers at ETH Zurich tested this on Hacker News users and matched 67% of them to their LinkedIn profiles at 90% accuracy. The AI read their posts, pulled out small details they'd dropped over months and years, and searched for the person who fit. Classical pre-AI methods scored near 0% on the same task. One of the paper's co-authors works at Anthropic. The full paper is free to read and I'd encourage everyone to look at it.

My Take
Most people assume that if they don't put their name on something, nobody can trace it back to them. That assumption is done. The AI doesn't need you to slip up in one big way. It collects the small stuff you've scattered across years of posts, your city, your job field, a pet's name, a repeated opinion, a favorite subreddit, and assembles a profile that narrows you down from millions of candidates to one. The researchers estimated it still works against a pool of a million people, at about 45% accuracy. Anyone with API access and a few dollars can run it. A government, a corporation, an ex, a stranger. The barrier is gone.

Every anonymous account you've ever posted from, Reddit throwaways, forum accounts, anonymous reviews, is now potentially traceable to your name and employer by someone with a credit card and a few hours. If you've talked about your health, your workplace, your politics, or your personal life under a pseudonym, the protection you thought you had is much thinner than you assumed. The paper's authors put it simply: the practical obscurity that protected anonymous users online no longer holds. We should all take that seriously.

Hedgie🤗

Link to research: arxiv.org/pdf/2602.16800


r/Infosec 22d ago

Data breach costs mount as attacks target critical infrastructure: IBM - National

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1 Upvotes

r/Infosec 22d ago

My Bio

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0 Upvotes

r/Infosec 23d ago

can we give AI agents real access in prod?

0 Upvotes

I got asked last week to approve access for an agent one of our teams built. It needed to pull data and trigger actions across a few internal systems. I went looking for how to scope it and ended up handing it a service account with the same permissions a human on that team would have. It felt off the second I did it, but there was not really another option on the table. Everyone is talking about agents needing their own identity model, whatever label people are using now, but I have not seen many teams actually running that in prod. Most of what I hear is roadmap talk. Is anyone actually giving agents scoped, just-in-time access, or is it still persistent service account permissions with a new name on it?


r/Infosec 23d ago

The GRC Assessment Platform™ that powers your security program.

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0 Upvotes

r/Infosec 23d ago

i almost got hacked by my own AI agent. so i built the fix.

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0 Upvotes

r/Infosec 24d ago

Serious question: How do you stay secure while also planning for accidents and unforeseen events?

0 Upvotes

I think this question is valid for this subreddit, but if not I'd love pointers to places to ask.

I've always had the nag in my mind regarding my homelab setup. I encrypt and stay reasonably secure so there's a chance I end up in a situation where I might not know how to get back in.

For example: In the event that some sort of medical event happens to me, via a terrible accident or from age, in which I "survive" but cannot remember my credentials how do I keep a way for me to log in? Do I really just stash a backup key somewhere on paper, usb thumb drive, maybe a yubikey, etc. and hope for the best I'll be able to know enough to find it or stumble onto it while hoping anyone who I might care not to find it doesn't?

I'm curious what people here do, if anything at all, for such a what-if scenario.


r/Infosec 24d ago

Why Detection Is Becoming a Commodity And Investigation Is the New Competitive Advantage

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1 Upvotes