Defending Against Injection Attacks Through Context-Sensitive String Evaluation

By Tadeusz Pietraszek, Chris Vanden Berghe. International Symposium on Recent Advances in Intrusion Detection, 2005

394 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems

View Paper: https://www.semanticscholar.org/paper/cf031f0c47a3cf443b127ffe34f49db3a5700573

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Zhendong Su
2. Gary Wassermann
3. Adam Kiezun
4. Christopher Krügel
5. Giovanni Vigna
6. Philip J. Guo
7. Michael D. Ernst
8. Engin Kirda

In Information Systems

1. Zhendong Su
2. Gary Wassermann
3. Adam Kiezun
4. Giovanni Vigna
5. Christopher Krügel
6. Davide Balzarotti
7. Michael D. Ernst
8. Philip J. Guo

Citations in the corpus

• The essence of command injection attacks in web applications (2006, methodology): “Th re is also recent work on runtime taint tracking [31, 32].”
• Sound and precise analysis of web applications for injection vulnerabilities (2007, methodology): “[23] and Pietraszek and Berghe [24] propose to enforce the same policy for PHP more rigorously.”
• Taint-Enhanced Policy Enforcement: A Practical Approach to Defeat a Wide Range of Attacks (2006, methodology): “The implementations of [23] and [24] are very similar, using hand-transformation of the PHP interpreter to track taint data.”
• Dytan: a generic dynamic taint analysis framework (2007, background): “NguyenTuong and colleagues [18] propose an instance of this approach for PHP-based web applications, whereas Haldar, Chandra, and Franz [6], Pietraszek and Berghe [19], and Halfond and Orso [7] target applications written in Java.”
• Automatic creation of SQL Injection and cross-site scripting attacks (2009, background): “Dynamic monitoring tools [13,25,27] incur runtime overhead on the running application and do not detect vulnerabilities until the code has been deployed.”
• AMNESIA: analysis and monitoring for NEutralizing SQL-injection attacks (2005, result): “Two related approaches by Nguyen-Tuong and colleagues [20] and Pietraszek and Berghe [22] modify the PHP interpreter to track precise taint information about user input.”
• Saner: Composing Static and Dynamic Analysis to Validate Sanitization in Web Applications (2008, background): “Pietraszek and Vanden Berghe [33] present a unifying view of injection vulnerabilities and describe a general approach to the detection and prevention of injection attacks through the dynamic tracking of the flow of untrusted data inside an application.”
• Cross Site Scripting Prevention with Dynamic Data Tainting and Static Analysis (2007, neutral): “interpreter-based approaches for PHP are presented in [23] and [26].”
• Pixy: a static analysis tool for detecting Web application vulnerabilities (2006, methodology): “Dynamic tools (e.g., [9] [18] [21], and Perl's taint mode try to detect attacks while executing the audited program, whereas static analyzers ([10] [11] [15] [16]) scan the Web application's source code for vulnerabilities.”