# sqlidps
### SQL Injection - Detection and Prevention System
<!---->
SQLIDPS is a tool designed to detect and prevent SQL injection attacks in web applications. SQL injection is a common attack vector that allows attackers to execute arbitrary SQL code on a database, potentially leading to data breaches and other security issues. This project aims to provide a robust solution for identifying and mitigating such vulnerabilities.
### Flow Chart
The data flow in SQLIDPS illustrates how user inputs are processed to detect and prevent SQL injection attacks.
Below is a detailed visualization of the flow:
📚 For more detailed documentation, visit [deepwiki docs](https://deepwiki.com/DPRIYATHAM/sqlidps/1-overview).
## 🚀 Performance Benchmark
**🛡️ SQL Injection Check Time:** **0.8ms per input**
## Usage
### `SQLi.check(data)`
Checks if the provided `data` contains potential SQLi payloads. Raises `PotentialSQLiPayload` if a malicious input is detected.
* **Arguments**:
* `data` (str | list | dict): Input to be checked.
* **Example**:
```python
from sqlidps import SQLi
try:
SQLi.check("SELECT * FROM users WHERE '1'='1' --")
except PotentialSQLiPayload as e:
print("Blocked:", e)
```
### `SQLi.parse(data: dict, error="potential payload") → dict`
Parses a dictionary and replaces any malicious values with a safe error string instead of raising an exception.
* **Arguments**:
* `data` (dict): Dictionary to scan.
* `error` (str): Replacement string for detected payloads (default: `"potential payload"`).
* **Returns**:
* A cleaned dictionary with malicious values replaced.
* **Example**:
```python
data = {
"username": "admin",
"password": "' OR '1'='1"
}
cleaned = SQLi.parse(data)
print(cleaned)
# Output: {'username': 'admin', 'password': 'potential payload'}
```
## Installing
```bash
pip install sqlidps
```
## Build from Source
```bash
cd sqlidps
pip install -r requirements.txt
flex -o sqlidps/lex.yy.c sqlidps/lexer.l
make sqlidps && make sqlidps clean
python sqlidps/train.py
pip install .
```
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"description": "# sqlidps\n\n\n\n\n\n\n\n\n\n\n### SQL Injection - Detection and Prevention System\n<!---->\nSQLIDPS is a tool designed to detect and prevent SQL injection attacks in web applications. SQL injection is a common attack vector that allows attackers to execute arbitrary SQL code on a database, potentially leading to data breaches and other security issues. This project aims to provide a robust solution for identifying and mitigating such vulnerabilities.\n\n### Flow Chart\nThe data flow in SQLIDPS illustrates how user inputs are processed to detect and prevent SQL injection attacks. \nBelow is a detailed visualization of the flow:\n\n\n\n\n\ud83d\udcda For more detailed documentation, visit [deepwiki docs](https://deepwiki.com/DPRIYATHAM/sqlidps/1-overview).\n\n## \ud83d\ude80 Performance Benchmark\n**\ud83d\udee1\ufe0f SQL Injection Check Time:** **0.8ms per input**\n\n## Usage\n\n### `SQLi.check(data)`\n\nChecks if the provided `data` contains potential SQLi payloads. Raises `PotentialSQLiPayload` if a malicious input is detected.\n\n* **Arguments**:\n\n * `data` (str | list | dict): Input to be checked.\n\n* **Example**:\n\n```python\nfrom sqlidps import SQLi\n\ntry:\n SQLi.check(\"SELECT * FROM users WHERE '1'='1' --\")\nexcept PotentialSQLiPayload as e:\n print(\"Blocked:\", e)\n```\n### `SQLi.parse(data: dict, error=\"potential payload\") \u2192 dict`\n\nParses a dictionary and replaces any malicious values with a safe error string instead of raising an exception.\n\n* **Arguments**:\n\n * `data` (dict): Dictionary to scan.\n * `error` (str): Replacement string for detected payloads (default: `\"potential payload\"`).\n\n* **Returns**:\n\n * A cleaned dictionary with malicious values replaced.\n\n* **Example**:\n```python\ndata = {\n \"username\": \"admin\",\n \"password\": \"' OR '1'='1\"\n}\n\ncleaned = SQLi.parse(data)\nprint(cleaned)\n# Output: {'username': 'admin', 'password': 'potential payload'}\n```\n## Installing \n```bash\npip install sqlidps\n```\n\n## Build from Source\n```bash\ncd sqlidps\npip install -r requirements.txt\nflex -o sqlidps/lex.yy.c sqlidps/lexer.l\nmake sqlidps && make sqlidps clean\npython sqlidps/train.py\npip install .\n```\n\n",
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