Do these 3 things before closing this tab:
1Scan for outdated or missing drivers - takes under a minute2Clear out junk files and repair common Windows errors3Fix the driver behind crashes, sound loss and screen glitchesSqlStealthRogue is a command-line utility for extracting data through a SQL or NoSQL injection point that a tester already knows about. Its “zero-probe” design means it skips discovery requests: the project says each request is intended to extract data, using database and query details supplied by the operator. It is therefore a focused tool for authorized testing, not an injection-point scanner.
What “zero-probe” means
The project describes SqlStealthRogue as a minimalist SQL/NoSQL injection data dumper for cases where the injection point and relevant database, table, or column details are already known. Its README characterizes the design this way: “every single request it sends is a data-extraction request.” That is the project’s description of its intended workflow, not an independently verified guarantee about every request or configuration.
As an Amazon Associate I earn from qualifying purchases.
The tool is presented as a single-entry Python program using the standard library, with no dependencies. The repository identifies it as MIT-licensed. Its premise trades discovery for preparation: the tester supplies context rather than asking the program to find an injection point or infer the target structure.
What extraction methods the project lists
The README describes five categories of extraction approach. These are feature descriptions from the project, not instructions for testing a system without authorization.
#1 Best Overall
- Union-based: retrieves data by incorporating it into a compatible query result.
- Error-based: uses database error behavior to expose information.
- Boolean-blind: infers information from differences in how the application responds to true and false conditions.
- Time-based: infers information from response delays. The project says this mode runs serially to avoid stacking delays on the target.
- NoSQL prefix: uses regular-expression conditions to recover values by matching prefixes.
The project also describes configurable templates, tamper plugins, HTTP keep-alive, and controls for parallelism. Those options do not remove the need to understand the injection context or to keep testing within an approved scope.
Database and service coverage: what the README claims
The project’s README labels its compatibility table a “12-Engine Real-Machine Verification Matrix.” It lists these engines and services, while also identifying caveats within the matrix. This is the project’s own account of testing; it should not be read as independent certification.
| Engine or service listed | Qualification in the project’s account |
|---|---|
| MySQL 8 | Listed in the project’s matrix; individual technique results and qualifications are reported there. |
| PostgreSQL 14 | Listed in the project’s matrix. The README also cites PostgreSQL conditions in its large-chunk performance claim. |
| MSSQL 2022 | Listed in the project’s matrix. The README also cites MSSQL conditions in its large-chunk performance claim. |
| SQLite | Listed in the project’s matrix; individual technique results and qualifications are reported there. |
| Redis | Listed in the project’s matrix; its time-based template is described as shipped but not lab-verified. |
| MongoDB 7 | Listed in the project’s matrix; individual technique results and qualifications are reported there. |
| openGauss 5 | Listed in the project’s matrix; individual technique results and qualifications are reported there. |
| OceanBase CE | Listed in the project’s matrix; individual technique results and qualifications are reported there. |
| Oracle 23ai | The README says XMLType errors no longer echo data in this version; older versions may behave differently. |
| Elasticsearch 8 | Listed in the project’s matrix; its time-based template is described as shipped but not lab-verified. |
| Milvus 2.4 | Listed in the project’s matrix; individual technique results and qualifications are reported there. |
| pgvector | Listed in the project’s matrix; individual technique results and qualifications are reported there. |
The README marks some techniques as disabled based on what the project calls real-machine evidence. Because results and caveats vary by engine and method, the list of engines alone does not establish that every extraction mode works against every listed target.
Limitations that affect recovered data
- Blind extraction is byte-wise. The project warns that blind modes can mangle multibyte characters, so recovered text may not preserve the original character sequence.
- Bit-parallel extraction has a termination edge case. The README says an all-zero byte is treated as the end of a string; values containing that byte may therefore be truncated or otherwise misrepresented.
- Time-based extraction is serial. The project says it avoids parallelizing delays so that they do not stack on the target. This is a design constraint, not a promise of a particular completion time.
- Incorrect context can fail quietly. Without the error-mark option, a wrong configuration may simply produce no extracted rows, according to the README.
- Engine behavior can change the result. For example, the project specifically notes the Oracle 23ai XMLType error behavior, while warning that older versions may differ.
How to read the project’s speed figures
The README reports that bit-parallel blind extraction is 5.35× faster than serial binary search while using the same number of requests, and that HTTP keep-alive is 5.6× faster. It also reports a reduction from 22 requests to 6 for a 600-character value under its stated PostgreSQL/MSSQL large-chunk conditions. These are figures claimed by the SqlStealthRogue project, not independently reproduced results. The README’s conditions matter: they should not be generalized into expected performance for another engine, application, network, or value.
When this tool’s workflow fits—and when it does not
SqlStealthRogue’s stated workflow fits a narrow stage of an authorized assessment: an injection point is already identified, and the relevant database or query details are known well enough to configure extraction. It is not presented as a way to discover vulnerabilities or map an unknown application.
That distinction separates its stated focus from broader testing workflows. The sqlmap usage documentation describes testing across union, error, boolean-blind, and time-based techniques, with separate switches for non-SQL injection classes such as NoSQL, as well as adjustable detection level and risk. It warns that higher-risk tests can have unwanted effects in some query contexts. The NoSQLMap repository describes an auditing and attack-automation tool focused on NoSQL injection and default-configuration weaknesses, with documented emphasis on MongoDB and CouchDB. These projects describe different scopes; those differences do not establish that one tool universally replaces or outperforms another.
Rank #4
Authorization and responsible use
The SqlStealthRogue README says: “For authorized security testing only. Using this tool against systems you do not have written permission to test is illegal. You are solely responsible for your actions.” This is the project’s warning, not a jurisdiction-specific legal analysis. Use the utility only within a clearly authorized scope, with written permission from the system owner, and follow the engagement’s rules for data access and handling.
PC Slower Than It Used to Be?
A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11Crashes, No Sound, or Screen Glitches?
Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteQuick Recap
Best Value
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
