18 citations · 21 across the 2 of their papers we have counts for
6 papers
Ulysses: A Security Harness For Synthesizing Verifiable Web Exploits
Aditya Oke, André Vicente Duarte, Rui Melo +6
How can an AI agent automatically discover security vulnerabilities in any software repository? Existing approaches use LLMs to generate software vulnerability exploits. However, i…
Self-Evolving Static Analysis via LLM Pseudo-Labeling
Rui Melo, Andre Duarte, Aditya Oke +5
Security bugs often slip past static analysis not because they are impossible to detect, but because detection rules have not yet been written for the code in front of us. New fram…
When Models Know but Can't Linearly Say: Relational Encoding Limits Linear Vulnerability Classification in Code LLMs
Rui Melo, Andre Catarino, Claudia Mamede +2
Large language models can detect vulnerable code, yet the form of vulnerability encoding in their representations remains unclear. We analyze 8 code models spanning 6.7B-15B parame…
ABSENTIA: Detecting Broken Access Control Vulnerabilities in Web Applications
André V. Duarte, Aditya Oke, Rui Melo +7
Broken access control, the failure of authorization, is one of the most prevalent web security risks. Unlike injection, a flow of untrusted input into a dangerous operation, author…
SaulLM-54B & SaulLM-141B: Scaling Up Domain Adaptation for the Legal Domain
Pierre Colombo, Telmo Pires, Malik Boudiaf +7
In this paper, we introduce SaulLM-54B and SaulLM-141B, two large language models (LLMs) tailored for the legal sector. These models, which feature architectures of 54 billion and…
SaulLM-7B: A pioneering Large Language Model for Law
Pierre Colombo, Telmo Pessoa Pires, Malik Boudiaf +8
In this paper, we introduce SaulLM-7B, a large language model (LLM) tailored for the legal domain. With 7 billion parameters, SaulLM-7B is the first LLM designed explicitly for leg…