How SRC gangsters exploit vulnerabilities Preliminary information collection As the old saying goes, the essence of penetration testing is information collection. For weak players without 0day, mining SRC feels more like sorting out the company’s assets. We often need to spend a long time to collect information, collect and Information related to this company, includingthe […]
Tag: src
openpnp – src – preliminary analysis of the configuration file loading process
Article directory openpnp – src – preliminary analysis of the configuration file loading process Overview notes The git version for your own compilation Error screenshot Question 1 – How to locate the first scene where an exception is thrown in debugging mode? Combined with the scene found during single-step debugging, we can analyze the cause […]
How SRC gangsters exploit vulnerabilities
Table of Contents Early information collection Subdomain name collection and website information collection Collect subdomains through github js information collection Some tips for picking out medium and low-risk vulnerabilities Some common vulnerabilities in the login box Weak password vulnerability Common information leakage vulnerabilities Other OWASPTop10 vulnerabilities Submission of Threat Intelligence Some thoughts on discovering high-risk […]
Solving cv2.error: C:\projects\opencv-python\opencv\modules\imgproc\src\resize.cpp:4044: error: (-215) s
Table of Contents Solve cv2.error: C:\projects\opencv-python\opencv\modules\imgproc\src\resize.cpp:4044: error: (-215) s error wrong reason Solution Sample code: Implementing an image scaling application grammar Parameter Description return value Interpolation method Example Solution to cv2.error: C:\projects\opencv-python\opencv\modules\imgproc\src\resize.cpp:4044: error: (-215) s error When we use the ??cv2.resize()?? function of the OpenCV library to resize the image, sometimes we may encounter the […]
Solving cv2.error: OpenCV(4.1.2) C:\projects\opencv-python\opencv\modules\imgproc\src\color.cpp:182: error
Table of Contents Solve cv2.error: OpenCV(4.1.2) C:\projects\opencv-python\opencv\modules\imgproc\src\color.cpp:182: error problem wrong reason Solution 1. Check the image path 2. Check image format 3. Check image color space conversion 4. Update OpenCV version 5. Install OpenCV-contrib in conclusion RGB color space HSV color space YCrCb color space Solve cv2.error: OpenCV(4.1.2) C:\projects\opencv-python\opencv\modules\imgproc\src\color.cpp:182: error problem When using the OpenCV […]
Thoughts on SRC concurrency vulnerability mining
1.Burpsuite Turbo plug-in usage Turbo Intruder is a Burp Suite extension for sending large numbers of HTTP requests and analyzing their results. It is designed to complement Burp Intruder to handle attacks requiring special speed, duration or complexity. Major users exploit concurrency security vulnerabilities Enter the bp plug-in store to download the Turbo plug-in: Successful […]
The whole process of actual SRC vulnerability mining, detailed process [Network Security]
Foreword Record a complete actual combat of mining a certain SRC vulnerability, which lasted for more than a week. The article is a bit long, please read it patiently. It records the complete actual combat of SRC vulnerability mining. Penetration process Because the chosen lucky person did not plan the test scope, there is no […]
Validity test of new responsive image attributes srcset, sizes, and media
1. Write in front Test time: 2018/3/28 Testing tools and methods: Firefox developer edition-responsive design mode of mozila browser 2. Knowledge points involved CSS Media Queries-MDN Responsive images – srcset and sizes attributes Responsive images English information 1 English information 2 3. Summary of test items and results (1) Test pictures (100px, 300px, 600px, 800px) […]
Transformers library source code analysis: transformers/src/transformers/models/flaubert/modeling_flaubert.py
transformers/src/transformers/models/flaubert/modeling_flaubert.py # Copied from transformers.models.xlm.modeling_xlm.MultiHeadAttention class MultiHeadAttention(nn.Module): NEW_ID = itertools.count() def __init__(self, n_heads, dim, config): super().__init__() self.layer_id = next(MultiHeadAttention.NEW_ID) self.dim = dim self.n_heads = n_heads self.dropout = config.attention_dropout assert self.dim % self.n_heads == 0 self.q_lin = nn.Linear(dim, dim) self.k_lin = nn.Linear(dim, dim) self.v_lin = nn.Linear(dim, dim) self.out_lin = nn.Linear(dim, dim) self.pruned_heads = set() def prune_heads(self, […]