UCR Security Lab (@seclab-ucr)

Top repositories

1

INTANG

C
2,859
star
2

SymTCP

Automatic Discrepancy Discovery for DPI Elusion
Python
250
star
3

tcp_exploit

Off-Path TCP Exploit: How Wireless Routers Can Jeopardize Your Secret
JavaScript
105
star
4

KOOBE

Towards Facilitating Exploit Generation of Kernel Out-Of-Bounds Write Vulnerabilities
82
star
5

SUTURE

Precise and high-order static points-to/taint analysis based on LLVM IR.
C++
69
star
6

SADDNS

SADDNS: Side Channel Based DNS Cache Poisoning Attack
C
51
star
7

SyzDescribe

C++
50
star
8

LLift

The source code of project "LLift" (Enhancing static analysis with LLM)
Python
46
star
9

SyzGen_setup

Go
42
star
10

UBITect

C++
38
star
11

IncreLux

Progressive Scrutiny: Incremental Detection of UBI bugs in the Linux Kernel
C++
29
star
12

GPT-Expr

Assisting Static Analysis with Large Language Models: A ChatGPT Experiment
27
star
13

SyzBridge

SyzBridge is a research project that adapts Linux upstream PoCs to downstream distributions. It provides rich interfaces that allow you to do a lot of cool things with Syzbot bugs
Python
24
star
14

Themis

Themis: Ambiguity-Aware Network Intrusion Detection based on Symbolic Model Comparison
C++
20
star
15

ShadowBlock

Code release for our WWW 2019 paper entitled "ShadowBlock: A Lightweight and Stealthy Adblocking Browser".
C++
18
star
16

Unias

A Hybrid Alias Analysis
C++
18
star
17

K-LEAK

C++
14
star
18

SADDNS2.0

Go
11
star
19

CLAP

This repository hosts the implementation of CLAP (Context Learning-based Adversarial Protection) that is proposed in our CoNEXT 2020 paper titled "You Do (Not) Belong Here: Detecting DPI Evasion Attacks with Context Learning". The code here can be used to reproduce the main results in the paper.
Python
9
star
20

SyzGenPlusPlus

Python
8
star
21

SCENT

TCP Side Channel Excavation Tool
C++
7
star
22

CCS24Mesh

7
star
23

Patchlocator

An Investigation of the Android Kernel Patch Ecosystem Usenix security 21
Python
6
star
24

PAPP

Prefetcher-Aware Prime+Probe
C
5
star
25

A4

Code and dataset release for our ACSAC 2021 paper titled "Eluding ML-based Adblockers With Actionable Adversarial Examples".
HTML
5
star