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Record W2111273637 · doi:10.1109/wse.2009.5631226

WAFA: Fine-grained dynamic analysis of web applications

2009· article· en· W2111273637 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWeb Application Security Vulnerabilities
Canadian institutionsQueen's University
Fundersnot available
KeywordsComputer scienceSQL injectionParsingDatabaseDynamic web pageWeb applicationWeb application securitySQLWeb pageData WebWeb modelingWorld Wide WebWeb developmentProgramming languageQuery by Example

Abstract

fetched live from OpenAlex

Database interactions are a vital source of information in the analysis of highly dynamic systems such as web applications. Most web application security vulnerabilities, such as SQL injection and broken access control, can be traced to problems in database interactions. which are implemented as a set of embedded or constructed SQL statements. The identification and analysis of these embedded statements as an integral component of the host application requires complex analysis including robust parsing, pattern matching, control flow and data flow analysis. In this paper, we propose an approach to this problem using source transformation technology. A rich model of fine-grained information is extracted from dynamic web applications, allowing us to reason not only about the SQL embedded system, but also about page access, server environment variables, cookies and session management functions. We evaluate our system on the popular bulletin board web application PhpBB, a PHP / MySQL-based dynamic web application.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.938
Threshold uncertainty score0.351

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.265
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations27
Published2009
Admission routes1
Has abstractyes

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