AI Agent Attack Surface: Every Pass Through the Loop Is a Way In
How an AI agent differs from a chatbot, its 5 parts, the ReAct loop and its input and output channels, plus a lab to fingerprint an agent over its API.
I'm Bikramjeet Singh, a Lead Penetration Tester. Every engagement teaches something the courses skip over, so I write those bits down in full, web, API, Active Directory, cloud, Kubernetes and AI, including the attempts that went nowhere. No theory, no vendor filler, no "it depends".
Newest first. Each one starts with something I did not understand, works through what actually happens under the hood, and ends with what it means for security. The wrong turns stay in.
How an AI agent differs from a chatbot, its 5 parts, the ReAct loop and its input and output channels, plus a lab to fingerprint an agent over its API.
How Entra ID, AWS and Google Cloud log people and apps in, where keys and tokens hide on a test, how to reuse them in a lab, and what to check on each.
What AWS, Microsoft and Google let you test in a cloud pentest: permitted services, banned attacks, approval forms, reporting windows and a scoping checklist.
CVE-2026-111497 (Node2Shell) is a CVSS 9.2 Brotli decoder overflow in Node.js, now in CISA KEV. Learn the root cause, who is exposed and how to check and patch.
Everything I publish lands on one of these. The count is the honest depth, not a target.
Cluster security learned in public, start to finish. The series is complete.
Attacking and securing AI systems and the plumbing around them.
Fresh CVEs pulled apart to root cause, not "patch now".
IAM, storage exposure and config reviews that matter.
App and API testing, auth flaws and business logic abuse.
Active Directory, lateral movement, privilege paths.
Coming soonKiosk escapes, restricted shells, thick client, mobile.
Coming soonWPA handshakes, evil twin, deauth, Bluetooth and RFID.
Coming soonEvery live track has a command-level playbook. The real checks, the exact commands, what a hit looks like and the honest gotcha, ordered the way a test runs from recon to cleanup. Each note stands on its own, there's a tick-box checklist you can run mid-engagement, and live search across the lot. Cloud sorts by AWS, Azure and Google Cloud.
The OWASP LLM path: prompt injection, jailbreaks, data and output handling, agents and tools.
The full attack path: recon, in-pod enumeration, escalation, escape, cleanup, plus the scanner and CIS tooling.
Sortable by AWS, Azure or Google Cloud, scoping and recon all the way down to cleanup.
AWS · Azure · GCPRecon to reporting: auth and sessions, access control, injection, SSRF, client-side, API-specific.
Active Directory, lateral movement and privilege paths.
Coming soonWPA handshakes, evil twin, deauth, Bluetooth and RFID.
Coming soonKiosk escapes, restricted shells, thick client and mobile.
Coming soonEvery line below is a link to something already on this site. No roadmap, no coming soon, just what is published and how much of it there is.
A complete series: a cluster built, broken and rebuilt across 42 topics, from RBAC and admission control through to runtime.
How the models actually work, then how they fail, from neural network internals to attacking LLM apps.
Testing AWS, Azure and Google Cloud from the ground up, starting with what each service is really called.
Command-level operator playbooks: 254 AI / LLMs, 140 Kubernetes, 38 Cloud, 26 Web & API. The bits you reach for mid-engagement.
CVE teardowns taken to root cause rather than "patch now and hope".
Started the Kubernetes track in the open and kept going for 42 topics. The counts move because I publish, not because I planned a number.
New write-up most days. Labs, dead ends and the odd working exploit. Compare notes, argue with me, or just come along for the ride.