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programanalysis-ggnn

Design and Implementation of Program Semantic Analysis System Based on Deep Learning and Data Flow Graph [GGNN]

pulp-riscv-binutils-gdb

pulp-riscv-gnu-toolchain

pulp-riscv-newlib

rcatt

A python app to predict Att&ck tactics and techniques from cyber threat reports

reversecore

《逆向工程核心原理》代码及案例

riscv-dejagnu

DejaGnu RISC-V port

riscv-glibc

RISC-V port of GNU's libc

secure-ijtag

secverilog

seqtrans

SeqTrans: Automatic Vulnerability Fix via Sequence to Sequence Learning

shellshock-apt

side-channel-attack

A demo of Flush-Reload style Side-channel attack.

skyfull

soft-practice

软件工程作业

spade

SPADE: Support for Provenance Auditing in Distributed Environments

specfuzz

A tool to enable fuzzing for Spectre vulnerabilities

spectre-poc

Spectre (CVE-2017-5753) (CVE-2017-5715). Not By Me. Collected from Book.

spectre-without-shared-memory

spectreoootest

sql-practice

stone

《两周自制脚本语言》源代码

tee

This is (TEE)Trusted Execution Environment , I search those and try to build it and recode the some ARM Developer

tensorflow-train

A demo modified from tensorflow 0.7 documents for study

threatrace

treelstm

Tree-structured Long Short-Term Memory networks (http://arxiv.org/abs/1503.00075)

trustsecsicode

A hardware-software co-design framework for easing the economy of meeting the new generation of embedded systems requirements. Arm TrustZone technology is exploited to implement the root of trust of a virtualization-based architecture that allows the execution of a General Purpose Operating System (GPOS) side-by-side with a Real-Time Operating System (RTOS). RTOS services were offloaded to hardware,so that we can present simultaneous improvements on performance and determinism. Instead of focusing in a concrete application, we provide a complete framework, specifically tailored for Zynq-base devices, that developers can use to accelerate a bunch of distinct applications across different embedded industries.

trustzone-secverilog

Verifying TrustZone with SecVerilog

ttpdrill-0.3

TTPDrill focuses on developing automated and context-aware analytics of cyber threat intelligence to accurately learn attack patterns (TTPs) from commonly available CTI sources in order to timely implement cyber defense actions.