Research

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Oversight Behavior Eval

Python, Inspect AI
  • Scheming detection evaluation testing whether language models exhibit differential transparency based on perceived oversight level.
  • Built with UK AISI’s Inspect framework. 12 scenarios across 4 categories with model-graded scoring and statistical analysis.

LLMCodeProbe

Python, CrossHair, Z3, Hypothesis
  • Finds bugs in LLM generated code that test suites miss. Tested against benchmark solutions from HumanEval, MBPP, and SWE-Bench.
  • Uses symbolic execution, property-based testing, and boundary analysis to measure the correctness gap - percentage of passing solutions with hidden bugs.

SpecEval

Python, Docker, Claude/OpenAI, DeepSeek
  • Multi language formal specification inference benchmark evaluating how well LLMs generate pre/post conditions and invariants.
  • Supports Java (JML), C (ACSL), Rust (Prusti), and Solidity (SMTChecker) with Docker-based verification. Extended from FormalBench, and added new metrics: minimality, strength.

SKLEE

C, LLVM, KLEE
Research intern, IIT Delhi
  • Dynamic symbolic analysis tool for Ethereum smart contracts built on KLEE. Detects integer overflow, unchecked send, and contract vulnerabilities through formal verification.
  • Extended implementation to macOS and categorized vulnerability coverage.

Motion2NX

C++
Research assistant, Cryptography and Information Security lab, IISc
  • Modified MOTION2NX (Mixed-Protocol Secure Two-Party Computation framework) to support multiple parties data computation. Modified Yao’s garbled circuits protocol for three-party computation.

Pseudo Random Number Generation using Cellular Automata

C++, TestU01
Summer intern, NIT Trichy and IEST Shibpur
  • Analyzed the properties of a cellular automaton (CA) to develop an efficient random Number Generator.
  • Devised algorithm to generate rules of a 10-state CA PRNG satisfying randomness properties. Verified randomness using Dieharder battery, NIST Statistical Test suite via TestU01: https://github.com/darshana-v/TestU01

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