English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Buffer-overruns are a prevalent vulnerability in software libraries andapplications. Fuzz testing is one of the effective techniques to detectvulnerabilities in general. Greybox fuzzers such as AFL automatically generatea sequence of test inputs for a given program using a fitness-guided searchprocess. A recently proposed approach in the literature introduced abuffer-overrun specific fitness metric called "headroom", which tracks howclose each generated test input comes to exposing the vulnerabilities. Thatapproach showed good initial promise, but is somewhat imprecise and expensivedue to its reliance on conservative points-to analysis. Inspired by theapproach above, in this paper we propose a new ground-up approach for detectingbuffer-overrun vulnerabilities. This approach uses an extended version of ASAN(Address Sanitizer) that runs in parallel with the fuzzer, and reports back tothe fuzzer test inputs that happen to come closer to exposing buffer-overrunvulnerabilities. The ASAN-style instrumentation is precise as it has nodependence on points-to analysis. We describe in this paper our approach, aswell as an implementation and evaluation of the approach.

HDR-Fuzz: Detecting Buffer Overruns using AddressSanitizer Instrumentation and Fuzzing