• Title/Summary/Keyword: Dirty cow

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A study on Dirty Pipe Linux vulnerability

  • Tanwar, Saurav;Kim, Hee Wan
    • International Journal of Internet, Broadcasting and Communication
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    • v.14 no.3
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    • pp.17-21
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    • 2022
  • In this study, we wanted to examine the new vulnerability 'Dirty Pipe' that is founded in Linux kernel. how it's exploited and what is the limitation, where it's existed, and overcome techniques and analysis of the Linux kernel package. The study of the method used the hmark[1] program to check the vulnerabilities. Hmark is a whitebox testing tool that helps to analyze the vulnerability based on static whitebox testing and automated verification. For this purpose of our study, we analyzed Linux kernel code that is downloaded from an open-source website. Then by analyzing the hmark tool results, we identified in which file of the kernel it exists, cvss level, statistically depicted vulnerabilities on graph which is easy to understand. Furthermore, we will talk about some software we can use to analyze a vulnerability and how hmark software works. In the case of the Dirty Pipe vulnerability in Linux allows non-privileged users to execute malicious code capable of a host of destructive actions including installing backdoors into the system, injecting code into scripts, altering binaries used by elevated programs, and creating unauthorized user profiles. This bug is being tracked as CVE-2022-0847 and has been termed "Dirty Pipe"[2] since it bears a close resemblance to Dirty Cow[3], and easily exploitable Linux vulnerability from 2016 which granted a bad actor an identical level of privileges and powers.

A Technique for Accurate Detection of Container Attacks with eBPF and AdaBoost

  • Hyeonseok Shin;Minjung Jo;Hosang Yoo;Yongwon Lee;Byungchul Tak
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.6
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    • pp.39-51
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    • 2024
  • This paper proposes a novel approach to enhance the security of container-based systems by analyzing system calls to dynamically detect race conditions without modifying the kernel. Container escape attacks allow attackers to break out of a container's isolation and access other systems, utilizing vulnerabilities such as race conditions that can occur in parallel computing environments. To effectively detect and defend against such attacks, this study utilizes eBPF to observe system call patterns during attack attempts and employs a AdaBoost model to detect them. For this purpose, system calls invoked during the attacks such as Dirty COW and Dirty Cred from popular applications such as MongoDB, PostgreSQL, and Redis, were used as training data. The experimental results show that this method achieved a precision of 99.55%, a recall of 99.68%, and an F1-score of 99.62%, with the system overhead of 8%.

Studies on Infection Rate and Causative Agents of Bovine Mastitis in Kangweon Area (강원지역의 젖소 유방염 감염율 및 원인균에 관한 연구)

  • Goh Gwang-Du;Kim Doo
    • Journal of Veterinary Clinics
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    • v.8 no.1
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    • pp.47-52
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    • 1991
  • A total of 2,024 quarters of 515 dairy cattle in Kangweon area were examined for incidence of subclinical mastitis. Milk samples from cattle infected with subclinical mastitis were studied bacteriologically and the bacterial strains isolated were further examined for sensitivity to 12 antibacterial agents. And the status of carrying out the mastitis control program in 28 dairy farms was examined. The results obtained were summerized as follows ; 1. A total of 308(59.8%) of 515 cattle and 656(32.4%) of 2,024 quarters were found to be infected with subclinical mastitis. 2. The 277 strains of etiological agents were isolated from 358 subclinical quarters. These were identified as Staphylococcus aureus(14.4%), other staphylococci(36.5%), Streptoccus agalatiae(8.7%), other streptococci(30.7%), Bacillus spp.(1.8%), Corynebacterium spp.(1.4%) and coliform(0.7%). 3. The 109 strains of streptococci and 141 strains of staphylococci were examined for sensitivity to 12 antibacterial agents. All the strains of streptococci were sensitive to penicillin, ampicillin and cephalothin, and they were also sensitive to erythromycin(88.1%), clindamycin(83.5%), enrofloxacin(75.2%), trimethoprim+sulfamethoxazole(67.9%), The strains of staphylococci were sensitive to cephalothin(97.2%), gentamicin(83.0%). enroflozacin(80.9%), trimethoprim+sulfamethoxazole(78.0%), erythromycin(71.6%) and clindamycin(71.6%). But all the strains resisted to colistin. 4. In the 28 dairy farms examined, condition of udder before washing was dirty in most of the farms (89.7%). Hygiene of milking equipment was only good in the 5 farms(17.9%). Teat preparation before milking was good in the 6 farms(21.4%). The farms in which teat dipping after milking was conducted were 46.4%. Dry cow treatment for the complete herd was carried out in most of the farms(89.3%) but mastitis checking was only carried out in the 8 farms(28.6%) irregularly.

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Analytical studies of bovine mastitis management by standard plate counts(SPC) and somatic cell counts(SCC) (젖소 유방염 관리에 따른 세균 및 체세포수 등급 실태 조사 분석)

  • 허정호;정명호;박영호;조명희;이주홍
    • Korean Journal of Veterinary Service
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    • v.21 no.3
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    • pp.285-300
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    • 1998
  • 1. The number of average milking cows, clinical forms of mastitis, mastitis-developing cows, and cows killed by mastitis a year were 25.7, 1.8(7%), 6.3(26%), and 2.7(10.1%)heads, respectively. The annual grade changes of standard plate counts(SPC) and somatic cell counts(SCC) showed the grade 1A of SPC diminished sharply from April to August, we think it was due to the lack of proper management in farming season and the grade 3 of SCC indirectly influenced increased in huge during August. 2. The average number of parturitions of farms was 2.3, but 50% of below 1 parturition were 22 farms(31%), 50% of above 3 parturitions were 16(23%) out of 71 farms. According to grades of the number of parturitions of milking cows per each farm, the farms' grades recording 3 parturitions and 50% were little bit excellent. 3. The actual situation research of foremilking CMT revealed 35 out of 74 farmer didn't do CMT Among them(35 out of 74 farmers), 80% did not test thanks to the troublesome process of the CMT. SCC grade 3, among farms who did foremilking CMT once or twice a month and who did not were 29% and 40% respectively and SPC grade 1A were 55% and 9%, respectively. 4. The research of actual situation on milking management let us know 29 farms(39%) did not do lastmilking, 37 farms(49%) usually did overmilking, and 34 farms(46%) did milking for 4 or 5 minutes. Grades according to average requiring times of milking showed SCC grade 1 of farms milking within 7 minutes was 11% and SPC grade 1A was 34%, on the other side, farms milking more than 7 minutes were 0% in SCC grade 1 and 13% in SPC grade 1A. Grades according to the starting time of milking after rubbing teats showed SPC grade 1A of farms starting milking at about 1 minute and over 2 minutes were 50% and 20%, respectively. 5. The research of actual situation on hygienic milking management uncovered 65 farms(88%) were using one towel which was used in washing teats and udders to wash more than 3 to 4 cows, and 53 farms(72%) were using one dried towel to dry udders not for each cow but for more than 3 to 4 cows after washing. Also, on milking turns disclosed 30 farms(40%) were milking cows in the order of incoming without isolation of a dominant group. According to grades of towels used in washing teats and udders, farms using a towel for each cow were 56% and a towel for over 3 cows were 31% in SPC grade 1A. According to using-or-not grades of dried towels after washing udders, farms using a towel for each cow were 79% and a towel for over 3 cows were 21% in SPC grade 1A. 6. Farms doing teat-dipping before milking were 7(10%), not doing teat-dipping after milking, or doing sometimes were 9(12%), and doing right after milking were 57(77%). And farms doing teat-dipping after dry cows and before delivery were 21(28a ). Farms using bethadine as an antiseptic solution were 70(95%), 40 farms(59%) diluted it with water as weak as 5 to 10 times, and on drying cows 64 farms(87%) slowly did it more than 2 days. Grade 1A of SPC of farms doing teat-dipping at every milking was 38%, farms doing occasionally or not was 33%, and farms doing it right after milking was 37% and doing after milking more than 5 cows was 20%. Grade 1A of SPC among farms diluting bethadine 5 times and diluting 5 to 10 times with water were 36% and 33%, respectively, and Grade 3 of SCC were 35% and 32%, respectively. 7. Studies on nonlactating period medical treatment, as the cows were on dry, 54 farms treated with their own hands.73 farms(98%) had bovine mastitis treated for themselves. And on applying medicines against mastitis, 55 farmers chose them on the basis of their own experience, 42 farms(57%) were treated more than 3 days. 41 farms(55%) dumped away the mastitis infected milk separately, 24 farms(32%) were feeding and milking at the same time. 8. Fifty-six farms(76%) always washed and disinfected milking machines after milking. Farms using the milking machines at low, or variable vacuum pressures, or at the vacuum pressure, set at the moment of its installation were 31(42%), and farms that did not know pulsation ratio were 27(37%). Farms changing liners when they were torn 8(11%), 58 farms(78%) said they checked milking system when there were wrong with them, 31 farms(42%) changed milking hoses when they found out problems, and 42 farms(57%) cleaned vacuum and milking systems when they felt dirty. The SPC grade 1A of farms washing and sterilizing milking machines was 38% and farms only washing was 28%.

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