Danjun Liu

Dr. Danjun Liu

National University of Defense Technology, Changsha, Guangdong, China
orcid

Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
5 December 2022 in IEEE Transactions on Information Forensics and Security
Verified
Journal Article
Closed access
DLDanjun Liu
Danjun Liu
PWPengfei Wang
Pengfei Wang
XZXu Zhou
Xu Zhou
WXWei Xie
Wei Xie
GZGen Zhang
Gen Zhang
BWBaosheng Wang
Baosheng Wang
Vulnerability fixing is time-consuming, hence, not all of the discovered vulnerabilities can be fixed timely. In reality, developers prioritize vulnerability fixing based on exploitability. Large numbers of vulnerabilities are delayed to patch or even ignored as they are regarded as “unexploitable” or underestimated owing to the difficulty in exploiting the weak primitives. However, exploits may have been in the wild. In this paper, to exploit the weak primitives that traditional approaches fail to exploit, we propose a versatile exploitation strategy that can transform weak exploit primitives into strong exploit primitives. Based on a special object in the kernel named Thanos object, our approach can exploit a UAF vulnerability that does not have function pointer dereference and an OOB write vulnerability that has limited write length and value. Our approach overcomes the shortage that traditional exploitation strategies heavily rely on the capability of the vulnerability. To facilitate using Thanos objects, we devise a tool named TAODE to automatically search for eligible Thanos objects from the kernel. Then, it evaluates the usability of the identified Thanos objects by the complexity of the constraints. Finally, it pairs vulnerabilities with eligible Thanos objects. We have evaluated our approach with real-world kernels. TAODE successfully identified numerous Thanos objects from Linux. Using the identified Thanos objects, we proved the feasibility of our approach with 20 real-world vulnerabilities, most of which traditional techniques failed to exploit. Through the experiments, we find that in addition to exploiting weak primitives, our approach can sometimes bypass the kernel SMAP mechanism (CVE-2016-10150, CVE-2016-0728), better utilize the leaked heap pointer address (CVE-2022-25636), and even theoretically break certain vulnerability patches (e.g., double-free).

30 August 2018
Verified
Book Chapter
Closed access
PDF file
DLDanjun Liu
Danjun Liu
YTYong Tang
Yong Tang
BWBaosheng Wang
Baosheng Wang
WXWei Xie
Wei Xie
BYBo Yu
Bo Yu

22 November 2022 in Applied Sciences
Verified
Journal Article
Open access
PDF file
DLDanjun Liu
Danjun Liu
PWPengfei Wang
Pengfei Wang
XZXu Zhou
Xu Zhou
BWBaosheng Wang
Baosheng Wang
Since a large number of Linux kernel vulnerabilities are discovered every year, many vulnerabilities cannot be patched in time. Security vendors often prioritize patching high-risk vulnerabilities, and the ratings of vulnerabilities need to be evaluated based on factors such as exploitability and the scope of influence. However, evaluating exploitability is challenging and time-consuming, especially for race vulnerabilities, whose exploitation process is complicated and the success rate of exploitation is low, making them more likely to be overlooked. In this paper, we propose a new framework, called ERACE, to facilitate the process of exploiting kernel race vulnerabilities. Given a program called a proof of concept (PoC) that can trigger a race vulnerability, ERACE first applies a combination of dynamic and static analysis techniques to locate the instruction that causes the race. Then, it applies code instrumentation and static analysis to determine the timing relationship between the race instructions and the triggering type of the vulnerability and records the vulnerability context information. Next, it uses backward taint analysis to identify checkpoints that can be used to determine whether the race condition and heap spraying are satisfied and records the system calls to which the checkpoints belong. Finally, we can generate exploits based on the information collected above. To demonstrate the utility of ERACE, we tested it on 23 real-world vulnerabilities. As a result, we successfully detected the race points of 19 vulnerabilities, the timing relationship among the race instructions, and the triggering types of 17 vulnerabilities and succeeded in generating exploits for 13 vulnerabilities. ERACE can effectively help security researchers simplify the analysis process of kernel race vulnerabilities, select appropriate exploitation methods, and use checkpoints to increase the success rates of exploitations.

16 May 2025
Verified
Book Chapter
Closed access
PDF file
QLQian Liu
Qian Liu
LZLei Zhou
Lei Zhou
XZXu Zhou
Xu Zhou
YWYuan Wei
Yuan Wei
DLDanjun Liu
Danjun Liu
ZWZhendong Wu
Zhendong Wu

22 November 2024 in Computers & Security
Verified
Journal Article
Closed access
DLDanjun Liu
Danjun Liu
XMXuan Meng
Xuan Meng
PWPengfei Wang
Pengfei Wang
XZXu Zhou
Xu Zhou
WXWei Xie
Wei Xie
BWBaosheng Wang
Baosheng Wang

1 January 2026 in IEEE Transactions on Information Forensics and Security
Verified
Journal Article
Closed access
LXLukai Xu
Lukai Xu
BWBaosheng Wang
Baosheng Wang
BYBo Yu
Bo Yu
DLDanjun Liu
Danjun Liu
PWPengfei Wang
Pengfei Wang
RLRunhao Liu
Runhao Liu