🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits significant risks related to network and shell operations, suggesting potential malicious activities such as data exfiltration or unauthorized command execution. Additionally, there's a strong indication of typosquatting, targeting 'pip', which increases suspicion.

High network risk
High shell risk
Potential typosquatting

Per-check LLM notes

Network: The network call to an external server suggests potential data exfiltration or C2 communication.
Shell: Executing arbitrary commands and capturing terminal panes indicates high risk of unauthorized access or behavior.
Obfuscation: The code uses base64 decoding and writes the decoded data to files, which could be used for obfuscating data but is also common in legitimate scenarios like handling binary files.
Credentials: No clear patterns indicative of credential harvesting were found.
Metadata: High risk due to potential typosquatting and lack of maintainer history.
⚠ Typosquatting target: pip

📦 Package Quality Overall: Low (4.6/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

1 test file(s) detected (e.g. test_durability.py)

◈ Medium Documentation 5.0

Some documentation present

Detailed PyPI description (4403 chars)

○ Low Contributing Guide 4.0

No contributing guide or governance files found

Development Status classifier >= Beta

◈ Medium Type Annotations 7.0

Partial type annotation coverage

Classifier: Typing :: Typed
224 type-annotated function signatures detected in source

○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

No GitHub repository linked — contributor count unavailable

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

> bool: try: with urllib.request.urlopen(f"{SERVER_URL}/api/health", timeout=1) as r:

⚠ Code Obfuscation score 6.0

Found 3 obfuscation pattern(s)

nstance(img.data, bytes) else base64.b64decode(img.data) pathlib.Path(filename).write_bytes(data)
nstance(img.data, bytes) else base64.b64decode(img.data) ) pathlib.Path(filename).w
nstance(vid.data, bytes) else base64.b64decode(vid.data) pathlib.Path(filename).write_bytes(data)

⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

s.stdout.flush() result = subprocess.run(cmd, cwd=directory, env=env) print() sys.stdout.flus
s.stdout.flush() result = subprocess.run( _sample_cmd(sample), env=_sample_env(sample
r]: try: result = subprocess.run( _sample_cmd(sample), env=_sample_en
ure_pane() -> str: return subprocess.check_output( ["tmux", "capture-pane", "-t", SESSION, "-p"], text
keys(*keys: str) -> None: subprocess.run(["tmux", "send-keys", "-t", SESSION, *keys], check=True) d
ef cleanup() -> None: subprocess.run( ["tmux", "kill-session", "-t", SESSION],

✓ Credential Harvesting

No credential harvesting patterns detected

⚠ Typosquatting score 10.0

Possible typosquat of: pip, six, arq, rq

"ai" is 2 edit(s) from "pip"
"ai" is 2 edit(s) from "six"
"ai" is 2 edit(s) from "arq"
"ai" is 2 edit(s) from "rq"

✓ Registered Email Domain

Email domain looks legitimate: vercel.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 6.0

3 maintainer concern(s) found

Only one version has ever been released — brand new package
Author name is missing or very short
Author "" appears to have only 1 package on PyPI (new or inactive account)

✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with ai

Create a conversational chatbot named 'EchoBot' using the Python package 'ai'. EchoBot should be designed to interact with users through text-based conversations, providing information, answering questions, and engaging in simple dialogues. The goal is to demonstrate the versatility of the 'ai' package in handling natural language processing tasks, managing user interactions, and integrating external APIs for enhanced functionality.

Step 1: Set up your development environment with Python and install the 'ai' package. Ensure you have all necessary dependencies installed as well.

Step 2: Design the basic structure of EchoBot. Define classes or functions that will handle initialization, user input processing, response generation, and session management.

Step 3: Implement a simple question-answering system where EchoBot can answer predefined questions. Use the 'ai' package's capabilities to parse and understand user queries, and generate appropriate responses based on a knowledge base you create.

Step 4: Enhance EchoBot's interaction capabilities by adding support for context-aware responses. This means EchoBot should be able to remember previous parts of the conversation to provide more relevant answers or continue the dialogue naturally.

Step 5: Integrate an external API service (such as OpenWeatherMap for weather updates) to allow EchoBot to fetch real-time data and incorporate it into its responses. Utilize the 'ai' package to handle API calls and process the received data appropriately.

Step 6: Add a feature that allows EchoBot to learn from user interactions over time. This could involve updating its knowledge base based on new information provided by users or improving its understanding of user intent through machine learning techniques supported by the 'ai' package.

Throughout the project, focus on leveraging the 'ai' package's core features such as natural language understanding, context management, and integration with external services to create a seamless and intelligent conversational experience.