Name
Abstract | ||
|---|---|---|
ABSTRACTPrototype pollution is a type of vulnerability specific to prototype-based languages, such as JavaScript, which allows an adversary to pollute a base object’s property, leading to a further consequence such as Denial of Service (DoS), arbitrary code execution, and session fixation. On one hand, the only prior work in detecting prototype pollution adopts dynamic analysis to fuzz package inputs, which inevitably has code coverage issues in triggering some deeply embedded vulnerabilities. On the other hand, it is challenging to apply state-of-the-art static analysis in detecting prototype pollution because of the involvement of prototype chains and fine-grained object relations including built-in ones. In this paper, we propose a flow-, context-, and branch-sensitive static taint analysis tool, called ObjLupAnsys, to detect prototype pollution vulnerabilities. The key of ObjLupAnsys is a so-called object lookup analysis, which gradually expands the source and sink objects into big clusters with a complex inner structure by performing targeted object lookups in both clusters so that a system built-in function can be redefined. Specifically, at the source cluster, ObjLupAnsys proactively creates new object properties based on how the target program uses the initial source object; at the sink cluster, ObjLupAnsys assigns property values in object lookups to decrease the number of object lookups to reach a system built-in function. We implemented an open-source tool and applied it for the detection of prototype pollution among Node.js packages. Our evaluation shows that ObjLupAnsys finds 61 zero-day, previously-unknown, exploitable vulnerabilities as opposed to 18 by the state-of-the-art dynamic fuzzing tool and three by a state-of-the-art static analysis tool that is modified to detect prototype pollution. To date, 11 vulnerable Node.js packages are assigned with CVE numbers and five have already been patched by their developers. In addition, ObjLupAnsys also discovered seven applications or packages including a real-world, online website, which are indirectly vulnerable due to the inclusion of vulnerable packages found by ObjLupAnsys. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1145/3468264.3468542 | FSE |
Keywords | DocType | Citations |
Abstract Interpretation, Prototype Pollution, Object Lookup Analysis, JavaScript | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Song Li | 1 | 0 | 0.68 |
| Mingqing Kang | 2 | 0 | 0.34 |
| Jianwei Hou | 3 | 6 | 3.15 |
| Yinzhi Cao | 4 | 297 | 18.73 |