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Description: 利用德国HALCON低层二次开发的视觉软件！可判别有与无，角度，坐标，等等！(use; utilize; take advantage of; exploit; avail oneself of
Germany; Deutschland
develop; open up; exploit; empolder
vision; visual sense; sense of sight; visus; seeing
software
distinguish; discriminate; differentiate
being and not being
angle; point of view
coordinate
wait a minute; etc; and so on; and so on and so forth; etcetera)
Platform: |
Size: 3933184 |
Author: yaozhi |
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Description: vulnerability prices for compare
Platform: |
Size: 442368 |
Author: thekraken |
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Description: arcgis平台addin插件 显示图斑的平方米、亩、公顷(ArcGIS Desktop Add-in exploit)
Platform: |
Size: 183296 |
Author: deep_sky |
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Description: 基于4.14.7内核的centos7和ubuntu16.04文件读取漏洞exploit。编译之后通过本地执行来利用漏洞。(Centos7 and ubuntu16.04 file read vulnerability exploit based on 4.14.7 kernel. After compilation, we exploit the vulnerability through local execution.)
Platform: |
Size: 8192 |
Author: 晓明同学 |
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Description: POC:
POC，Proof ofConcept，中文意思是“观点证明”。这个短语会在漏洞报告中使用，漏洞报告中的POC则是一段说明或者一个攻击的样例，使得读者能够确认这个漏洞是真实存在的。
EXP:
EXP，Exploit，中文意思是“漏洞利用”。意思是一段对漏洞如何利用的详细说明或者一个演示的漏洞攻击代码，可以使得读者完全了解漏洞的机理以及利用的方法。
漏洞概述：
2018年2月1日，Adobe官方发布安全通报（APSA18-01）,声明Adobe Flash 28.0.0.137及其之前的版本，存在高危漏洞（CVE-2018-4878）(POC:
POC, Proof ofConcept, Chinese means "proof of opinion". This phrase is used in vulnerability reports, and POC in vulnerability reports is a description or an example of an attack that allows the reader to confirm that the vulnerability is real.
EXP:
EXP, Exploit, Chinese means "exploit". This means a detailed description of how vulnerabilities are exploited or a demo of vulnerability attack code that allows readers to fully understand the mechanism of vulnerabilities and how to exploit them.
Vulnerability overview:
On February 1, 2018, Adobe issued an official security bulletin (APSA18-01), stating that Adobe Flash 28.0.0.137 and its previous versions had high-risk vulnerabilities (CVE-2018-4878).)
Platform: |
Size: 1327104 |
Author: zz_1 |
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Description: 我的世界反作弊aac1.9.4版本
Combat - 战斗类
- AutoClicker - 连点器
- KillAura - 杀戮光环
- MultiAction - 射箭/吃东西时攻击
- Criticals - 自动暴击- BowAimbot - 弓箭自动瞄准
Exploit - 漏洞类
- Some types of ServerCrasher - 一些类型的崩服器
Movement - 移动类
- Fly - 飞行
- LiquidWalk - 水上行走
- NoSlow - 使用物品时不减速
- SlimeJump - 粘液块飞行
- Speed - 加速
- Step - 快速走上方块
- Strafe - 灵活的移动
Player - 玩家类
- NoFall - 无摔落伤害
- FastUse 快速使用物品
Render - 地图类
- HealthTag - 血量显示
- PlayerESP - 玩家透视
- StorageESP - 箱子透视
- Freecam - 灵魂出窍
World - 世界类
- Scaffold - 自动搭路
- ChestStealer - 快速拿箱子(Combat - combat class
-Autoclicker - connector
-Killaura - the halo of killing
-Multi action - attack when archery / eating
-Criticals - Auto crit - bowaimbot - bow auto aim
Exploit - vulnerability class
-Some types of servercrasher
Move - move class
-Fly - flying
-Liquidwalk - walking on water
-Noslow - do not slow down when using items
-Slimejump - slime block flight
-Speed - acceleration
-Step - get on the block quickly
-Strafe - flexible mobility
Player - player class
-Nofall - no fall damage
-Fastuse fast use items
Render - map class
-Healthtag - blood volume display
-Player ESP - player Perspective
-Storageesp - box Perspective
-Freecam - out of body
World - world class
-Scaffold - Autopass
-Cheststeeler - get the box quickly)
Platform: |
Size: 539648 |
Author: 红石233 |
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Description: The mifare Classic is a contactless smart card that is used extensively in access control for office buildings, payment systems for public transport, and other applications. We reverse engineered the security mechanisms of this chip: the authentication protocol, the symmetric cipher, and the initialization mechanism. We describe several security vulnerabilities in these mechanisms and exploit these vulnerabilities with two attacks; both are capable of retrieving the secret key from a genuine reader. The most serious one recovers the secret key from just one or two authentication attempts with a genuine reader in less than a second on ordinary hardware and without any pre-computation. Using the same methods, an attacker can also eavesdrop the communication between a tag and a reader, and decrypt the whole trace, even if it involves multiple authentications. This enables an attacker to clone a card or to restore a real card to a previous state.
Platform: |
Size: 510586 |
Author: AlipayLogin_2088002498429280 |
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Description: Similar to other digital assets, deep neural network
(DNN) models could suffer from piracy threat initiated by insider
and/or outsider adversaries due to their inherent commercial
value. DNN watermarking is a promising technique to mitigate
this threat to intellectual property. This work focuses on black-
box DNN watermarking, with which an owner can only verify
his ownership by issuing special trigger queries to a remote
suspicious model. However, informed attackers, who are aware
of the watermark and somehow obtain the triggers, could
forge fake triggers to claim their ownerships since the poor
robustness of triggers and the lack of correlation between the
model and the owner identity. This consideration calls for new
watermarking methods that can achieve better trade-off for
addressing the discrepancy. In this paper, we exploit frequency
domain image watermarking to generate triggers and build our
DNN watermarking algorithm accordingly. Since watermarking
in the frequency domain is high concealment and robust to
signal processing operation, the proposed algorithm is superior to
existing schemes in resisting fraudulent claim attack. Besides, ex-
tensive experimental results on 3 datasets and 8 neural networks
demonstrate that the proposed DNN watermarking algorithm
achieves similar performance on functionality metrics and better
performance on security metrics when compared with existing
algorithms.
Platform: |
Size: 374457 |
Author: bamzi334 |
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