Shangzhi Xu (The University of New South Wales), Jialiang Dong (The University of New South Wales), Weiting Cai (Delft University of Technology), Juanru Li (Feiyu Tech), Arash Shaghaghi (The University of New South Wales), Nan Sun (The University of New South Wales), Siqi Ma (The University of New South Wales)

Nowadays, software development progresses
rapidly to incorporate new features. To facilitate such growth
and provide convenience for developers when creating and
updating software, reusing open-source software (i.e., thirdparty
library reuses) has become one of the most effective
and efficient methods. Unfortunately, the practice of reusing
third-party libraries (TPLs) can also introduce vulnerabilities
(known as 1-day vulnerabilities) because of the low maintenance
of TPLs, resulting in many vulnerable versions remaining in
use. If the software incorporating these TPLs fails to detect the
introduced vulnerabilities and leads to delayed updates, it will
exacerbate the security risks. However, the complicated code
dependencies and flexibility of TPL reuses make the detection of
1-day vulnerability a challenging task. To support developers in
securely reusing TPLs during software development, we design
and implement VULTURE, an effective and efficient detection
tool, aiming at identifying 1-day vulnerabilities that arise from
the reuse of vulnerable TPLs. It first executes a database creation
method, TPLFILTER, which leverages the Large Language
Model (LLM) to automatically build a unique database for the
targeted platform. Instead of relying on code-level similarity
comparison, VULTURE employs hashing-based comparison to
explore the dependencies among the collected TPLs and identify
the similarities between the TPLs and the target projects.
Recognizing that developers have the flexibility to reuse TPLs
exactly or in a custom manner, VULTURE separately conducts
version-based comparison and chunk-based analysis to capture
fine-grained semantic features at the function levels. We applied
VULTURE to 10 real-world projects to assess its effectiveness
and efficiency in detecting 1-day vulnerabilities. VULTURE
successfully identified 175 vulnerabilities from 178 reused TPLs.

View More Papers

Revisiting EM-based Estimation for Locally Differentially Private Protocols

Yutong Ye (Institute of software, Chinese Academy of Sciences & Zhongguancun Laboratory, Beijing, PR.China.), Tianhao Wang (University of Virginia), Min Zhang (Institute of Software, Chinese Academy of Sciences), Dengguo Feng (Institute of Software, Chinese Academy of Sciences)

Read More

BARBIE: Robust Backdoor Detection Based on Latent Separability

Hanlei Zhang (Zhejiang University), Yijie Bai (Zhejiang University), Yanjiao Chen (Zhejiang University), Zhongming Ma (Zhejiang University), Wenyuan Xu (Zhejiang University)

Read More

Ring of Gyges: Accountable Anonymous Broadcast via Secret-Shared Shuffle

Wentao Dong (City University of Hong Kong), Peipei Jiang (Wuhan University; City University of Hong Kong), Huayi Duan (ETH Zurich), Cong Wang (City University of Hong Kong), Lingchen Zhao (Wuhan University), Qian Wang (Wuhan University)

Read More

Impact Tracing: Identifying the Culprit of Misinformation in Encrypted...

Zhongming Wang (Chongqing University), Tao Xiang (Chongqing University), Xiaoguo Li (Chongqing University), Biwen Chen (Chongqing University), Guomin Yang (Singapore Management University), Chuan Ma (Chongqing University), Robert H. Deng (Singapore Management University)

Read More