AI agent security · researchAmherst, MA / Tirupati, IN

SAHIR

how i got herethe long version

We are handing real decisions to systems that can't prove what they did.

Shaik Ahamed Sahir. I work on the security of autonomous AI agents — tamper-evident audit trails, how multi-agent systems collude when told not to, and attacks that silence the agents built to catch them. Incoming MS CS at UMass Amherst; B.Tech CSE from Sri Venkateswara University. One paper published, one in submission, one still open.

scroll ` for a shell
01

About

EngineerDeveloperResearcherOss Contributor

I came to security research from building. The question that moved me was narrow and wouldn't close: when an autonomous agent tells you what it did, what makes that account trustworthy? Not persuasive — verifiable. Most agent logs today are written by the same system they're meant to hold accountable, which makes them a record of intent, not evidence. That gap is what I work on: cryptographic audit trails that survive an adversary, and a clear-eyed account of how agents behave when they think no one can check.

CurrentlyIncoming MS CS @ UMass Amherst (Fall 2026)
ResearchingTamper-evident audit trails, multi-agent collusion, adversarial attacks on AI security agents
Building — open-source audit layer for AI agent systems
PublishedIEEE IATMSI 2026 · one paper in submission · one ongoing
Open toResearch collaborations and lab conversations
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Stack

React Next.js TypeScript Node.js MongoDB GSAP Rust Cryptography (Ed25519/SHA-256)
Python C WebGL Git Figma Linux
scroll faster. the letters can feel it.
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Work

the tools, the papers, and the work that led to both.

01 / the open questions

Research

Published — IEEE IATMSI 2026

AgentOps Replay

Event-sourced backend capturing every agent execution step, with real-time replay — any failure reproducible in under 2 clicks.

FastAPI · React · PostgreSQL · AWSView DOI ↗
In Submission — DOI Pending

Tesserae & FACADE

A cryptographic audit layer for multi-agent systems (Tesserae), paired with a taxonomy of exactly how agents collude even after you tell them not to (FACADE).

Rust · Ed25519 · Hash chains
Ongoing Research

VIABLE

An attack that makes AI security agents silently stop searching the web — without tripping any of the five detectors built to catch it.

Adversarial ML · AI Security Agents
Peer-reviewed record · 5 papers · 4 first/sole-authorGoogle Scholar ↗
02 / what the research ships as

Build

InfrastructureOpen Source

Your AI agent logs are not evidence. Sasana makes them defensible.

Rust · SHA-256 · Hash chainsGitHub ↗
FrontendLive

Shyniq

An e-commerce storefront for jewelry cleaners, built for real customers, not a portfolio demo.

Next.js · React · TailwindCSSVisit site ↗
BackendGitHub available soon

Multi-Agent Research Platform

A multi-agent pipeline — planner, coder, reviewer, memory — that turns a research question into a working prototype in minutes, not hours.

Python · FastAPI · LangGraph · Qdrant · Docker
03 / patches sent upstream

Open Source

tldraw45K+ ★ · TypeScript, ProseMirror, React

Fixed bullet/ordered list rendering in rich text shapes

Root-caused to tiptap's ProseMirror layer after review cycles with the founder and core maintainers.

tiptap35K+ ★ · TypeScript, ProseMirror

2 merged fixes in typography and markdown serialization

Pipe characters inside inline code spans no longer break markdown table cells; plus opt-in RTL smart quote pairing for Arabic, Hebrew, and Urdu, with zero change to existing LTR behavior.

lexicalMeta · TypeScript · rich text framework

5 merged fixes across selection, Yjs sync, DnD compliance, and the playground

Yjs desync after clearing nodes, selection growing mid-collaboration, DecoratorTextNode formatting, dragover spec compliance, and a playground colour modal that dismissed on first click.

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Contact

research collaborations · PhD and lab conversations · anything on agent auditabilityWorking onthe same question?